feat: modify frontend

pyproject.toml

@@ -77,7 +77,6 @@ dependencies = [
     "pymilvus>=2.6.4",
     "pgvector>=0.4.1",
     "botocore>=1.42.39",
-    "litellm>=1.0.0",
 ]
 keywords = [
     "bot",

src/langbot/pkg/api/http/service/space.py

@@ -179,7 +179,7 @@ class SpaceService:
         space_url = space_config['url']
 
         session = httpclient.get_session()
-        async with session.get(f'{space_url}/api/v1/models', params={'page_size': 100}) as response:
+        async with session.get(f'{space_url}/api/v1/models') as response:
             if response.status != 200:
                 raise ValueError(f'Failed to get models: {await response.text()}')
             data = await response.json()

src/langbot/pkg/provider/modelmgr/modelmgr.py

@@ -4,7 +4,6 @@ import sqlalchemy
 import traceback
 
 from . import requester
-from .requesters import litellmchat
 from ...core import app
 from ...discover import engine
 from . import token
@@ -43,13 +42,6 @@ class ModelManager:
 
         requester_dict: dict[str, type[requester.ProviderAPIRequester]] = {}
         for component in self.requester_components:
-            # Skip components that use litellm_provider (they will use litellmchat.py instead)
-            if component.spec.get('litellm_provider'):
-                self.ap.logger.debug(
-                    f'Skipping Python class loading for {component.metadata.name} '
-                    f'(uses litellm_provider={component.spec.get("litellm_provider")})'
-                )
-                continue
             requester_dict[component.metadata.name] = component.get_python_component_class()
 
         self.requester_dict = requester_dict
@@ -268,34 +260,13 @@ class ModelManager:
         else:
             provider_entity = provider_info
 
-        # Get requester manifest to check for litellm_provider
-        requester_manifest = self.get_available_requester_manifest_by_name(provider_entity.requester)
-
-        # Build config from base_url
-        config = {'base_url': provider_entity.base_url}
-
-        # Check if requester manifest specifies litellm_provider
-        if requester_manifest and requester_manifest.spec.get('litellm_provider'):
-            # Use unified LiteLLMRequester with provider prefix
-            # Map litellm_provider (YAML spec) to custom_llm_provider (config)
-            config['custom_llm_provider'] = requester_manifest.spec['litellm_provider']
-            requester_inst = litellmchat.LiteLLMRequester(
-                ap=self.ap,
-                config=config,
-            )
-            self.ap.logger.debug(
-                f'Using LiteLLMRequester for {provider_entity.requester} '
-                f'with custom_llm_provider={config["custom_llm_provider"]}'
-            )
-        else:
-            # Use original requester class (for backward compatibility)
-            if provider_entity.requester not in self.requester_dict:
-                raise provider_errors.RequesterNotFoundError(provider_entity.requester)
-            requester_inst = self.requester_dict[provider_entity.requester](
-                ap=self.ap,
-                config=config,
-            )
+        if provider_entity.requester not in self.requester_dict:
+            raise provider_errors.RequesterNotFoundError(provider_entity.requester)
 
+        requester_inst = self.requester_dict[provider_entity.requester](
+            ap=self.ap,
+            config={'base_url': provider_entity.base_url},
+        )
         await requester_inst.initialize()
 
         token_mgr = token.TokenManager(name=provider_entity.uuid, tokens=provider_entity.api_keys or [])

src/langbot/pkg/provider/modelmgr/requester.py

@@ -67,8 +67,8 @@ class RuntimeProvider:
             if isinstance(result, tuple):
                 msg, usage_info = result
                 if usage_info:
-                    input_tokens = usage_info.get('prompt_tokens', 0)
-                    output_tokens = usage_info.get('completion_tokens', 0)
+                    input_tokens = usage_info.get('input_tokens', 0)
+                    output_tokens = usage_info.get('output_tokens', 0)
                 return msg
             else:
                 return result
@@ -128,6 +128,7 @@ class RuntimeProvider:
         start_time = time.time()
         status = 'success'
         error_message = None
+        # Note: Stream doesn't easily provide token counts, set to 0
         input_tokens = 0
         output_tokens = 0
 
@@ -142,15 +143,6 @@ class RuntimeProvider:
                 remove_think=remove_think,
             ):
                 yield chunk
-            # Extract usage from stream if available (stored by LiteLLM requester)
-            if query:
-                if query.variables is None:
-                    query.variables = {}
-                if '_stream_usage' in query.variables:
-                    usage_info = query.variables['_stream_usage']
-                    input_tokens = usage_info.get('prompt_tokens', 0)
-                    output_tokens = usage_info.get('completion_tokens', 0)
-                    del query.variables['_stream_usage']
         except Exception as e:
             status = 'error'
             error_message = str(e)

src/langbot/pkg/provider/modelmgr/requesters/litellmchat.py

@@ -1,397 +0,0 @@
-"""LiteLLM unified requester for chat, embedding, and rerank."""
-
-from __future__ import annotations
-
-import typing
-
-import litellm
-from litellm import acompletion, aembedding, arerank
-
-from .. import errors, requester
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class LiteLLMRequester(requester.ProviderAPIRequester):
-    """LiteLLM unified API requester supporting chat, embedding, and rerank."""
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': '',
-        'timeout': 120,
-        'custom_llm_provider': '',
-        'drop_params': False,
-        'num_retries': 0,
-        'api_version': '',
-    }
-
-    async def initialize(self):
-        """Initialize LiteLLM client settings."""
-        # LiteLLM doesn't require explicit client initialization
-        # Configuration is passed per-request via litellm params
-        pass
-
-    def _build_litellm_model_name(self, model_name: str, custom_llm_provider: str | None = None) -> str:
-        """Build LiteLLM model name with provider prefix if needed."""
-        provider = custom_llm_provider or self.requester_cfg.get('custom_llm_provider', '')
-        if provider:
-            # LiteLLM format: provider/model_name
-            return f'{provider}/{model_name}'
-        # If no custom provider, assume model_name already includes prefix or is OpenAI-compatible
-        return model_name
-
-    def _convert_messages(self, messages: typing.List[provider_message.Message]) -> list[dict]:
-        """Convert LangBot messages to LiteLLM/OpenAI format."""
-        req_messages = []
-        for m in messages:
-            msg_dict = m.dict(exclude_none=True)
-            content = msg_dict.get('content')
-
-            if isinstance(content, list):
-                for part in content:
-                    if isinstance(part, dict) and part.get('type') == 'image_base64':
-                        part['image_url'] = {'url': part['image_base64']}
-                        part['type'] = 'image_url'
-                        del part['image_base64']
-
-            req_messages.append(msg_dict)
-
-        return req_messages
-
-    def _process_thinking_content(self, content: str, reasoning_content: str | None, remove_think: bool) -> str:
-        """Process thinking/reasoning content.
-
-        Args:
-            content: The main content from response
-            reasoning_content: Separate reasoning content from model
-            remove_think: If True, remove thinking markers; if False, preserve them
-
-        Returns:
-            Processed content string
-        """
-        # Extract and handle thinking tags
-        if content and 'CRETIRE_REASONING_BEGINk' in content and 'CRETIRE_REASONING_ENDk' in content:
-            import re
-
-            think_pattern = r'CRETIRE_REASONING_BEGINk(.*?)CRETIRE_REASONING_ENDk'
-
-            if remove_think:
-                # Remove thinking tags and their content from output
-                content = re.sub(think_pattern, '', content, flags=re.DOTALL).strip()
-            # else: preserve thinking content as-is
-
-        # Handle separate reasoning_content field
-        # Currently we don't include reasoning_content in user-facing output regardless of remove_think
-        # because it's typically internal model reasoning, not user-visible thinking
-        return content or ''
-
-    def _extract_usage(self, response) -> dict:
-        """Extract usage info from LiteLLM response."""
-        usage = response.usage
-        return {
-            'prompt_tokens': usage.prompt_tokens or 0,
-            'completion_tokens': usage.completion_tokens or 0,
-            'total_tokens': usage.total_tokens or 0,
-        }
-
-    def _build_common_args(self, args: dict, include_retry_params: bool = True) -> dict:
-        """Apply common requester config to args dict."""
-        if self.requester_cfg.get('base_url'):
-            args['api_base'] = self.requester_cfg['base_url']
-        if self.requester_cfg.get('timeout'):
-            args['timeout'] = self.requester_cfg['timeout']
-        if include_retry_params:
-            if self.requester_cfg.get('drop_params'):
-                args['drop_params'] = self.requester_cfg['drop_params']
-            if self.requester_cfg.get('num_retries'):
-                args['num_retries'] = self.requester_cfg['num_retries']
-            if self.requester_cfg.get('api_version'):
-                args['api_version'] = self.requester_cfg['api_version']
-        return args
-
-    def _handle_litellm_error(self, e: Exception) -> None:
-        """Convert LiteLLM exceptions to RequesterError. Never returns, always raises."""
-        # Check more specific exceptions first (they inherit from base exceptions)
-        if isinstance(e, litellm.ContextWindowExceededError):
-            raise errors.RequesterError(f'上下文长度超限: {str(e)}')
-        if isinstance(e, litellm.BadRequestError):
-            raise errors.RequesterError(f'请求参数错误: {str(e)}')
-        if isinstance(e, litellm.AuthenticationError):
-            raise errors.RequesterError(f'API key 无效: {str(e)}')
-        if isinstance(e, litellm.NotFoundError):
-            raise errors.RequesterError(f'模型或路径无效: {str(e)}')
-        if isinstance(e, litellm.RateLimitError):
-            raise errors.RequesterError(f'请求过于频繁或余额不足: {str(e)}')
-        if isinstance(e, litellm.Timeout):
-            raise errors.RequesterError(f'请求超时: {str(e)}')
-        if isinstance(e, litellm.APIConnectionError):
-            raise errors.RequesterError(f'连接错误: {str(e)}')
-        if isinstance(e, litellm.APIError):
-            raise errors.RequesterError(f'API 错误: {str(e)}')
-        raise errors.RequesterError(f'未知错误: {str(e)}')
-
-    async def _build_completion_args(
-        self,
-        model: requester.RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-        stream: bool = False,
-    ) -> dict:
-        """Build common completion arguments for invoke_llm and invoke_llm_stream."""
-        req_messages = self._convert_messages(messages)
-        model_name = self._build_litellm_model_name(model.model_entity.name)
-        api_key = model.provider.token_mgr.get_token()
-
-        args = {
-            'model': model_name,
-            'messages': req_messages,
-            'api_key': api_key,
-        }
-        if stream:
-            args['stream'] = True
-            args['stream_options'] = {'include_usage': True}
-        self._build_common_args(args)
-        args.update(extra_args)
-
-        if funcs:
-            tools = await self.ap.tool_mgr.generate_tools_for_openai(funcs)
-            if tools:
-                args['tools'] = tools
-
-        return args
-
-    async def invoke_llm(
-        self,
-        query: pipeline_query.Query,
-        model: requester.RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-        remove_think: bool = False,
-    ) -> tuple[provider_message.Message, dict]:
-        """Invoke LLM and return message with usage info."""
-        args = await self._build_completion_args(model, messages, funcs, extra_args, stream=False)
-
-        try:
-            response = await acompletion(**args)
-
-            message_data = response.choices[0].message.model_dump()
-            if 'role' not in message_data or message_data['role'] is None:
-                message_data['role'] = 'assistant'
-
-            content = message_data.get('content', '')
-            reasoning_content = message_data.get('reasoning_content', None)
-            message_data['content'] = self._process_thinking_content(content, reasoning_content, remove_think)
-
-            if 'reasoning_content' in message_data:
-                del message_data['reasoning_content']
-
-            message = provider_message.Message(**message_data)
-            usage_info = self._extract_usage(response)
-
-            return message, usage_info
-
-        except Exception as e:
-            self._handle_litellm_error(e)
-
-    async def invoke_llm_stream(
-        self,
-        query: pipeline_query.Query,
-        model: requester.RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-        remove_think: bool = False,
-    ) -> provider_message.MessageChunk:
-        """Invoke LLM streaming and yield chunks."""
-        args = await self._build_completion_args(model, messages, funcs, extra_args, stream=True)
-
-        chunk_idx = 0
-        role = 'assistant'
-
-        try:
-            response = await acompletion(**args)
-            async for chunk in response:
-                # Check for usage chunk (final chunk with stream_options include_usage)
-                if hasattr(chunk, 'usage') and chunk.usage and (not hasattr(chunk, 'choices') or not chunk.choices):
-                    usage_info = {
-                        'prompt_tokens': chunk.usage.prompt_tokens or 0,
-                        'completion_tokens': chunk.usage.completion_tokens or 0,
-                        'total_tokens': chunk.usage.total_tokens or 0,
-                    }
-                    if query:
-                        if query.variables is None:
-                            query.variables = {}
-                        query.variables['_stream_usage'] = usage_info
-                    continue
-
-                if not hasattr(chunk, 'choices') or not chunk.choices:
-                    continue
-
-                choice = chunk.choices[0]
-                delta = choice.delta.model_dump() if hasattr(choice, 'delta') else {}
-                finish_reason = getattr(choice, 'finish_reason', None)
-
-                if 'role' in delta and delta['role']:
-                    role = delta['role']
-
-                delta_content = delta.get('content', '')
-                reasoning_content = delta.get('reasoning_content', '')
-
-                if reasoning_content:
-                    chunk_idx += 1
-                    continue
-
-                if chunk_idx == 0 and not delta_content and not delta.get('tool_calls'):
-                    chunk_idx += 1
-                    continue
-
-                chunk_data = {
-                    'role': role,
-                    'content': delta_content if delta_content else None,
-                    'tool_calls': delta.get('tool_calls'),
-                    'is_final': bool(finish_reason),
-                }
-
-                chunk_data = {k: v for k, v in chunk_data.items() if v is not None}
-                yield provider_message.MessageChunk(**chunk_data)
-                chunk_idx += 1
-
-        except Exception as e:
-            self._handle_litellm_error(e)
-
-    async def invoke_embedding(
-        self,
-        model: requester.RuntimeEmbeddingModel,
-        input_text: list[str],
-        extra_args: dict[str, typing.Any] = {},
-    ) -> tuple[list[list[float]], dict]:
-        """Invoke embedding and return vectors with usage info."""
-        model_name = self._build_litellm_model_name(model.model_entity.name)
-        api_key = model.provider.token_mgr.get_token()
-
-        args = {
-            'model': model_name,
-            'input': input_text,
-            'api_key': api_key,
-        }
-        self._build_common_args(args, include_retry_params=False)
-
-        if model.model_entity.extra_args:
-            args.update(model.model_entity.extra_args)
-
-        args.update(extra_args)
-
-        try:
-            response = await aembedding(**args)
-
-            embeddings = [d.embedding for d in response.data]
-            usage_info = self._extract_usage(response)
-
-            return embeddings, usage_info
-
-        except Exception as e:
-            self._handle_litellm_error(e)
-
-    async def invoke_rerank(
-        self,
-        model: requester.RuntimeRerankModel,
-        query: str,
-        documents: typing.List[str],
-        extra_args: dict[str, typing.Any] = {},
-    ) -> typing.List[dict]:
-        """Invoke rerank and return relevance scores."""
-        model_name = self._build_litellm_model_name(model.model_entity.name)
-        api_key = model.provider.token_mgr.get_token()
-
-        args = {
-            'model': model_name,
-            'query': query,
-            'documents': documents,
-            'api_key': api_key,
-            'top_n': min(len(documents), 64),
-        }
-        self._build_common_args(args, include_retry_params=False)
-
-        if model.model_entity.extra_args:
-            args.update(model.model_entity.extra_args)
-
-        args.update(extra_args)
-
-        try:
-            response = await arerank(**args)
-
-            results = []
-            for r in response.results:
-                results.append(
-                    {
-                        'index': r.get('index', 0),
-                        'relevance_score': r.get('relevance_score', 0.0),
-                    }
-                )
-
-            if results:
-                scores = [r['relevance_score'] for r in results]
-                min_score = min(scores)
-                max_score = max(scores)
-                if max_score - min_score > 1e-6:
-                    for r in results:
-                        r['relevance_score'] = (r['relevance_score'] - min_score) / (max_score - min_score)
-
-            return results
-
-        except Exception as e:
-            self._handle_litellm_error(e)
-
-    async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
-        """Scan models supported by the provider."""
-        import httpx
-
-        base_url = self.requester_cfg.get('base_url', '').rstrip('/')
-        timeout = self.requester_cfg.get('timeout', 120)
-
-        if not base_url:
-            raise errors.RequesterError('Base URL required for model scanning')
-
-        headers = {}
-        if api_key:
-            headers['Authorization'] = f'Bearer {api_key}'
-
-        models_url = f'{base_url}/models'
-
-        try:
-            async with httpx.AsyncClient(trust_env=True, timeout=timeout) as client:
-                response = await client.get(models_url, headers=headers)
-                response.raise_for_status()
-                payload = response.json()
-
-            models = []
-            for item in payload.get('data', []):
-                model_id = item.get('id')
-                if not model_id:
-                    continue
-
-                # Infer model type
-                normalized_id = (model_id or '').lower()
-                embedding_keywords = ('embedding', 'embed', 'bge-', 'e5-', 'm3e', 'gte-', 'text-embedding')
-                model_type = 'embedding' if any(kw in normalized_id for kw in embedding_keywords) else 'llm'
-
-                models.append(
-                    {
-                        'id': model_id,
-                        'name': model_id,
-                        'type': model_type,
-                    }
-                )
-
-            models.sort(key=lambda x: (x['type'] != 'llm', x['name'].lower()))
-
-            return {'models': models}
-
-        except httpx.HTTPStatusError as e:
-            raise errors.RequesterError(f'Model scan failed: {e.response.status_code}')
-        except httpx.TimeoutException:
-            raise errors.RequesterError('Model scan timeout')
-        except Exception as e:
-            raise errors.RequesterError(f'Model scan error: {str(e)}')

src/langbot/pkg/provider/modelmgr/requesters/litellmchat.yaml

@@ -1,64 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: litellm-chat
-  label:
-    en_US: LiteLLM (Unified)
-    zh_Hans: LiteLLM (统一请求器)
-  icon: litellm.svg
-spec:
-  config:
-  - name: base_url
-    label:
-      en_US: Base URL
-      zh_Hans: 基础 URL
-    type: string
-    required: false
-    default: ''
-  - name: timeout
-    label:
-      en_US: Timeout
-      zh_Hans: 超时时间
-    type: integer
-    required: true
-    default: 120
-  - name: custom_llm_provider
-    label:
-      en_US: Custom Provider
-      zh_Hans: 自定义 Provider
-    type: string
-    required: false
-    default: ''
-    description:
-      en_US: Force provider type (e.g., anthropic, openai, gemini)
-      zh_Hans: 强制指定 provider 类型（如 anthropic, openai, gemini）
-  - name: drop_params
-    label:
-      en_US: Drop Unsupported Params
-      zh_Hans: 丢弃不支持参数
-    type: boolean
-    required: false
-    default: false
-  - name: num_retries
-    label:
-      en_US: Number of Retries
-      zh_Hans: 重试次数
-    type: integer
-    required: false
-    default: 0
-  - name: api_version
-    label:
-      en_US: API Version
-      zh_Hans: API 版本
-    type: string
-    required: false
-    default: ''
-  support_type:
-  - llm
-  - text-embedding
-  - rerank
-  provider_category: unified
-execution:
-  python:
-    path: ./litellmchat.py
-    attr: LiteLLMRequester

src/langbot/pkg/provider/tools/toolmgr.py

@@ -57,6 +57,41 @@ class ToolManager:
 
         return tools
 
+    async def generate_tools_for_anthropic(self, use_funcs: list[resource_tool.LLMTool]) -> list:
+        """为anthropic生成函数列表
+
+        e.g.
+
+        [
+          {
+            "name": "get_stock_price",
+            "description": "Get the current stock price for a given ticker symbol.",
+            "input_schema": {
+              "type": "object",
+              "properties": {
+                "ticker": {
+                  "type": "string",
+                  "description": "The stock ticker symbol, e.g. AAPL for Apple Inc."
+                }
+              },
+              "required": ["ticker"]
+            }
+          }
+        ]
+        """
+
+        tools = []
+
+        for function in use_funcs:
+            function_schema = {
+                'name': function.name,
+                'description': function.description,
+                'input_schema': function.parameters,
+            }
+            tools.append(function_schema)
+
+        return tools
+
     async def execute_func_call(self, name: str, parameters: dict, query: pipeline_query.Query) -> typing.Any:
         """执行函数调用"""
 

tests/unit_tests/provider/__init__.py

@@ -1 +0,0 @@
-"""Provider requester tests"""

tests/unit_tests/provider/test_litellmchat.py

@@ -1,633 +0,0 @@
-"""
-Tests for LiteLLMRequester - unified requester for chat, embedding, and rerank.
-
-These tests verify:
-- Parameter building and LiteLLM API calls
-- Response processing and usage extraction
-- Error handling and exception translation
-- Model name building with provider prefix
-"""
-
-import pytest
-from unittest.mock import Mock, AsyncMock, patch
-
-import litellm
-
-from langbot.pkg.provider.modelmgr.requesters import litellmchat
-from langbot.pkg.provider.modelmgr import errors
-
-
-class MockRuntimeModel:
-    """Mock RuntimeLLMModel for testing"""
-
-    def __init__(self, model_name: str = 'gpt-4o', api_key: str = 'test-key'):
-        self.model_entity = Mock()
-        self.model_entity.name = model_name
-        self.model_entity.extra_args = {}
-        self.provider = Mock()
-        self.provider.token_mgr = Mock()
-        self.provider.token_mgr.get_token = Mock(return_value=api_key)
-
-
-class MockRuntimeEmbeddingModel:
-    """Mock RuntimeEmbeddingModel for testing"""
-
-    def __init__(self, model_name: str = 'text-embedding-3-small', api_key: str = 'test-key'):
-        self.model_entity = Mock()
-        self.model_entity.name = model_name
-        self.model_entity.extra_args = {}
-        self.provider = Mock()
-        self.provider.token_mgr = Mock()
-        self.provider.token_mgr.get_token = Mock(return_value=api_key)
-
-
-class MockRuntimeRerankModel:
-    """Mock RuntimeRerankModel for testing"""
-
-    def __init__(self, model_name: str = 'cohere/rerank-english-v3.0', api_key: str = 'test-key'):
-        self.model_entity = Mock()
-        self.model_entity.name = model_name
-        self.model_entity.extra_args = {}
-        self.provider = Mock()
-        self.provider.token_mgr = Mock()
-        self.provider.token_mgr.get_token = Mock(return_value=api_key)
-
-
-class TestBuildLiteLLMModelName:
-    """Test _build_litellm_model_name method"""
-
-    def test_no_provider_prefix(self):
-        """Test model name without provider prefix"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={'custom_llm_provider': ''})
-        result = requester._build_litellm_model_name('gpt-4o')
-        assert result == 'gpt-4o'
-
-    def test_with_provider_prefix(self):
-        """Test model name with provider prefix"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={'custom_llm_provider': 'openai'})
-        result = requester._build_litellm_model_name('gpt-4o')
-        assert result == 'openai/gpt-4o'
-
-    def test_override_provider(self):
-        """Test override provider via parameter"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={'custom_llm_provider': 'openai'})
-        result = requester._build_litellm_model_name('claude-3', custom_llm_provider='anthropic')
-        assert result == 'anthropic/claude-3'
-
-
-class TestExtractUsage:
-    """Test _extract_usage method"""
-
-    def test_extract_usage_with_data(self):
-        """Test extraction with valid usage data"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        response = Mock()
-        response.usage = Mock()
-        response.usage.prompt_tokens = 100
-        response.usage.completion_tokens = 50
-        response.usage.total_tokens = 150
-
-        result = requester._extract_usage(response)
-
-        assert result['prompt_tokens'] == 100
-        assert result['completion_tokens'] == 50
-        assert result['total_tokens'] == 150
-
-    def test_extract_usage_with_zero_values(self):
-        """Test extraction when values are 0"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        response = Mock()
-        response.usage = Mock()
-        response.usage.prompt_tokens = 0
-        response.usage.completion_tokens = 0
-        response.usage.total_tokens = 0
-
-        result = requester._extract_usage(response)
-
-        assert result['prompt_tokens'] == 0
-        assert result['completion_tokens'] == 0
-
-
-class TestProcessThinkingContent:
-    """Test _process_thinking_content method"""
-
-    def test_no_thinking_markers(self):
-        """Test content without thinking markers"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        result = requester._process_thinking_content('Hello world', None, remove_think=True)
-        assert result == 'Hello world'
-
-    def test_remove_thinking_markers(self):
-        """Test removing thinking markers when remove_think=True"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        content = 'CRETIRE_REASONING_BEGINkLet me think...CRETIRE_REASONING_ENDk The answer is 42.'
-        result = requester._process_thinking_content(content, None, remove_think=True)
-        assert result == 'The answer is 42.'
-
-    def test_preserve_thinking_markers(self):
-        """Test preserving thinking markers when remove_think=False"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        content = 'CRETIRE_REASONING_BEGINkLet me think...CRETIRE_REASONING_ENDk The answer is 42.'
-        result = requester._process_thinking_content(content, None, remove_think=False)
-        assert 'CRETIRE_REASONING_BEGINk' in result
-        assert 'The answer is 42.' in result
-
-    def test_empty_content(self):
-        """Test empty content"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        result = requester._process_thinking_content('', None, remove_think=True)
-        assert result == ''
-
-
-class TestBuildCommonArgs:
-    """Test _build_common_args method"""
-
-    def test_build_args_with_all_params(self):
-        """Test building args with all config params"""
-        requester = litellmchat.LiteLLMRequester(
-            ap=Mock(),
-            config={
-                'base_url': 'https://api.openai.com/v1',
-                'timeout': 60,
-                'drop_params': True,
-                'num_retries': 3,
-                'api_version': '2024-01-01',
-            },
-        )
-
-        args = {}
-        requester._build_common_args(args)
-
-        assert args['api_base'] == 'https://api.openai.com/v1'
-        assert args['timeout'] == 60
-        assert args['drop_params'] == True
-        assert args['num_retries'] == 3
-        assert args['api_version'] == '2024-01-01'
-
-    def test_build_args_without_retry_params(self):
-        """Test building args without retry params for embedding/rerank"""
-        requester = litellmchat.LiteLLMRequester(
-            ap=Mock(),
-            config={
-                'base_url': 'https://api.openai.com/v1',
-                'timeout': 60,
-                'num_retries': 3,
-            },
-        )
-
-        args = {}
-        requester._build_common_args(args, include_retry_params=False)
-
-        assert args['api_base'] == 'https://api.openai.com/v1'
-        assert args['timeout'] == 60
-        assert 'num_retries' not in args
-
-
-class TestHandleLiteLLMError:
-    """Test _handle_litellm_error method"""
-
-    def test_bad_request_error(self):
-        """Test BadRequestError translation"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        # Create proper LiteLLM exception with required args
-        error = litellm.BadRequestError(message='test error', model='gpt-4o', llm_provider='openai')
-
-        with pytest.raises(errors.RequesterError) as exc_info:
-            requester._handle_litellm_error(error)
-
-        assert '请求参数错误' in str(exc_info.value)
-
-    def test_authentication_error(self):
-        """Test AuthenticationError translation"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        error = litellm.AuthenticationError(message='invalid key', model='gpt-4o', llm_provider='openai')
-
-        with pytest.raises(errors.RequesterError) as exc_info:
-            requester._handle_litellm_error(error)
-
-        assert 'API key 无效' in str(exc_info.value)
-
-    def test_rate_limit_error(self):
-        """Test RateLimitError translation"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        error = litellm.RateLimitError(message='rate limited', model='gpt-4o', llm_provider='openai')
-
-        with pytest.raises(errors.RequesterError) as exc_info:
-            requester._handle_litellm_error(error)
-
-        assert '请求过于频繁' in str(exc_info.value)
-
-    def test_timeout_error(self):
-        """Test Timeout translation"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        error = litellm.Timeout(message='timeout', model='gpt-4o', llm_provider='openai')
-
-        with pytest.raises(errors.RequesterError) as exc_info:
-            requester._handle_litellm_error(error)
-
-        assert '请求超时' in str(exc_info.value)
-
-    def test_context_window_error(self):
-        """Test ContextWindowExceededError translation"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        error = litellm.ContextWindowExceededError(message='context too long', model='gpt-4o', llm_provider='openai')
-
-        with pytest.raises(errors.RequesterError) as exc_info:
-            requester._handle_litellm_error(error)
-
-        assert '上下文长度超限' in str(exc_info.value)
-
-    def test_unknown_error(self):
-        """Test unknown error translation"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        with pytest.raises(errors.RequesterError) as exc_info:
-            requester._handle_litellm_error(Exception('unknown'))
-
-        assert '未知错误' in str(exc_info.value)
-
-
-class TestInvokeLLM:
-    """Test invoke_llm method"""
-
-    @pytest.mark.asyncio
-    async def test_invoke_llm_basic(self):
-        """Test basic LLM invocation"""
-        mock_ap = Mock()
-        mock_ap.tool_mgr = Mock()
-        mock_ap.tool_mgr.generate_tools_for_openai = AsyncMock(return_value=None)
-
-        requester = litellmchat.LiteLLMRequester(
-            ap=mock_ap,
-            config={
-                'base_url': 'https://api.openai.com/v1',
-                'timeout': 60,
-            },
-        )
-
-        model = MockRuntimeModel('gpt-4o', 'test-api-key')
-
-        # Mock LiteLLM response
-        mock_response = Mock()
-        mock_response.choices = [Mock()]
-        mock_response.choices[0].message = Mock()
-        mock_response.choices[0].message.model_dump = Mock(
-            return_value={
-                'role': 'assistant',
-                'content': 'Hello! How can I help you?',
-            }
-        )
-        mock_response.usage = Mock()
-        mock_response.usage.prompt_tokens = 10
-        mock_response.usage.completion_tokens = 20
-        mock_response.usage.total_tokens = 30
-
-        import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-        messages = [provider_message.Message(role='user', content='Hello')]
-
-        # Patch acompletion at the import location
-        with patch.object(litellmchat, 'acompletion', new_callable=AsyncMock, return_value=mock_response):
-            result_msg, usage = await requester.invoke_llm(
-                query=None,
-                model=model,
-                messages=messages,
-            )
-
-            assert result_msg.role == 'assistant'
-            assert result_msg.content == 'Hello! How can I help you?'
-            assert usage['prompt_tokens'] == 10
-            assert usage['completion_tokens'] == 20
-
-    @pytest.mark.asyncio
-    async def test_invoke_llm_with_tools(self):
-        """Test LLM invocation with function calling"""
-        mock_ap = Mock()
-        mock_ap.tool_mgr = Mock()
-        mock_ap.tool_mgr.generate_tools_for_openai = AsyncMock(
-            return_value=[{'type': 'function', 'function': {'name': 'get_weather'}}]
-        )
-
-        requester = litellmchat.LiteLLMRequester(ap=mock_ap, config={})
-
-        model = MockRuntimeModel('gpt-4o', 'test-api-key')
-
-        mock_response = Mock()
-        mock_response.choices = [Mock()]
-        mock_response.choices[0].message = Mock()
-        mock_response.choices[0].message.model_dump = Mock(
-            return_value={
-                'role': 'assistant',
-                'content': None,
-                'tool_calls': [
-                    {'id': 'call_123', 'type': 'function', 'function': {'name': 'get_weather', 'arguments': '{}'}}
-                ],
-            }
-        )
-        mock_response.usage = Mock()
-        mock_response.usage.prompt_tokens = 15
-        mock_response.usage.completion_tokens = 10
-        mock_response.usage.total_tokens = 25
-
-        import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-        import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-        messages = [provider_message.Message(role='user', content='What is the weather?')]
-        # Create proper LLMTool with all required fields
-        funcs = [Mock(spec=resource_tool.LLMTool)]
-        funcs[0].name = 'get_weather'
-        funcs[0].description = 'Get weather'
-
-        with patch.object(litellmchat, 'acompletion', new_callable=AsyncMock, return_value=mock_response):
-            result_msg, usage = await requester.invoke_llm(
-                query=None,
-                model=model,
-                messages=messages,
-                funcs=funcs,
-            )
-
-            assert result_msg.tool_calls is not None
-
-    @pytest.mark.asyncio
-    async def test_invoke_llm_error_handling(self):
-        """Test LLM invocation error handling"""
-        mock_ap = Mock()
-        mock_ap.tool_mgr = Mock()
-        mock_ap.tool_mgr.generate_tools_for_openai = AsyncMock(return_value=None)
-
-        requester = litellmchat.LiteLLMRequester(ap=mock_ap, config={})
-
-        model = MockRuntimeModel('gpt-4o', 'test-api-key')
-
-        import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-        messages = [provider_message.Message(role='user', content='Hello')]
-
-        error = litellm.AuthenticationError(message='invalid key', model='gpt-4o', llm_provider='openai')
-
-        with patch.object(litellmchat, 'acompletion', new_callable=AsyncMock, side_effect=error):
-            with pytest.raises(errors.RequesterError) as exc_info:
-                await requester.invoke_llm(
-                    query=None,
-                    model=model,
-                    messages=messages,
-                )
-
-            assert 'API key 无效' in str(exc_info.value)
-
-
-class TestInvokeEmbedding:
-    """Test invoke_embedding method"""
-
-    @pytest.mark.asyncio
-    async def test_invoke_embedding_basic(self):
-        """Test basic embedding invocation"""
-        requester = litellmchat.LiteLLMRequester(
-            ap=Mock(),
-            config={
-                'base_url': 'https://api.openai.com/v1',
-            },
-        )
-
-        model = MockRuntimeEmbeddingModel('text-embedding-3-small', 'test-api-key')
-
-        # Mock LiteLLM embedding response
-        mock_response = Mock()
-        mock_response.data = [
-            Mock(embedding=[0.1, 0.2, 0.3]),
-            Mock(embedding=[0.4, 0.5, 0.6]),
-        ]
-        mock_response.usage = Mock()
-        mock_response.usage.prompt_tokens = 20
-        mock_response.usage.completion_tokens = 0
-        mock_response.usage.total_tokens = 20
-
-        with patch.object(litellmchat, 'aembedding', new_callable=AsyncMock, return_value=mock_response):
-            embeddings, usage = await requester.invoke_embedding(
-                model=model,
-                input_text=['Hello', 'World'],
-            )
-
-            assert len(embeddings) == 2
-            assert embeddings[0] == [0.1, 0.2, 0.3]
-            assert embeddings[1] == [0.4, 0.5, 0.6]
-            assert usage['prompt_tokens'] == 20
-
-
-class TestInvokeRerank:
-    """Test invoke_rerank method"""
-
-    @pytest.mark.asyncio
-    async def test_invoke_rerank_basic(self):
-        """Test basic rerank invocation"""
-        requester = litellmchat.LiteLLMRequester(
-            ap=Mock(),
-            config={
-                'base_url': 'https://api.cohere.ai',
-            },
-        )
-
-        model = MockRuntimeRerankModel('rerank-english-v3.0', 'test-api-key')
-
-        # Mock LiteLLM rerank response
-        mock_response = Mock()
-        mock_response.results = [
-            {'index': 0, 'relevance_score': 0.95},
-            {'index': 1, 'relevance_score': 0.3},
-            {'index': 2, 'relevance_score': 0.8},
-        ]
-
-        with patch.object(litellmchat, 'arerank', new_callable=AsyncMock, return_value=mock_response):
-            results = await requester.invoke_rerank(
-                model=model,
-                query='What is the capital of France?',
-                documents=['Paris is the capital.', 'London is a city.', 'France is in Europe.'],
-            )
-
-            assert len(results) == 3
-            # Scores should be normalized
-            assert results[0]['index'] == 0
-            assert results[0]['relevance_score'] >= 0 and results[0]['relevance_score'] <= 1
-
-    @pytest.mark.asyncio
-    async def test_invoke_rerank_normalization(self):
-        """Test rerank score normalization"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        model = MockRuntimeRerankModel('rerank-english-v3.0', 'test-api-key')
-
-        # Mock response with varying scores
-        mock_response = Mock()
-        mock_response.results = [
-            {'index': 0, 'relevance_score': 0.9},
-            {'index': 1, 'relevance_score': 0.1},
-        ]
-
-        with patch.object(litellmchat, 'arerank', new_callable=AsyncMock, return_value=mock_response):
-            results = await requester.invoke_rerank(
-                model=model,
-                query='test query',
-                documents=['doc1', 'doc2'],
-            )
-
-            # After normalization: 0.9 -> 1.0, 0.1 -> 0.0
-            assert results[0]['relevance_score'] == 1.0
-            assert results[1]['relevance_score'] == 0.0
-
-    @pytest.mark.asyncio
-    async def test_invoke_rerank_single_document(self):
-        """Test rerank with single document (no normalization needed)"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        model = MockRuntimeRerankModel('rerank-english-v3.0', 'test-api-key')
-
-        mock_response = Mock()
-        mock_response.results = [
-            {'index': 0, 'relevance_score': 0.5},
-        ]
-
-        with patch.object(litellmchat, 'arerank', new_callable=AsyncMock, return_value=mock_response):
-            results = await requester.invoke_rerank(
-                model=model,
-                query='test query',
-                documents=['doc1'],
-            )
-
-            assert len(results) == 1
-            # Single score stays as is (min==max, no normalization)
-            assert results[0]['relevance_score'] == 0.5
-
-
-class TestConvertMessages:
-    """Test _convert_messages method"""
-
-    def test_convert_simple_message(self):
-        """Test converting simple text message"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-        messages = [provider_message.Message(role='user', content='Hello')]
-        result = requester._convert_messages(messages)
-
-        assert len(result) == 1
-        assert result[0]['role'] == 'user'
-        assert result[0]['content'] == 'Hello'
-
-    def test_convert_message_with_image_base64(self):
-        """Test converting message with image_base64 content"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-        messages = [
-            provider_message.Message(
-                role='user',
-                content=[
-                    {'type': 'text', 'text': 'What is in this image?'},
-                    {'type': 'image_base64', 'image_base64': 'data:image/png;base64,abc123'},
-                ],
-            )
-        ]
-        result = requester._convert_messages(messages)
-
-        assert len(result) == 1
-        content = result[0]['content']
-        assert isinstance(content, list)
-        # Check image_base64 converted to image_url
-        image_part = [p for p in content if p.get('type') == 'image_url'][0]
-        assert 'image_url' in image_part
-        assert image_part['image_url']['url'] == 'data:image/png;base64,abc123'
-
-    def test_convert_message_with_multiple_text_parts(self):
-        """Test converting message with multiple text parts (LiteLLM handles this)"""
-        requester = litellmchat.LiteLLMRequester(ap=Mock(), config={})
-
-        import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-        messages = [
-            provider_message.Message(
-                role='user',
-                content=[
-                    {'type': 'text', 'text': 'Hello'},
-                    {'type': 'text', 'text': 'World'},
-                ],
-            )
-        ]
-        result = requester._convert_messages(messages)
-
-        assert len(result) == 1
-        # LiteLLM handles multiple text parts, we pass them through
-        assert isinstance(result[0]['content'], list)
-
-
-class TestScanModels:
-    """Test scan_models method"""
-
-    @pytest.mark.asyncio
-    async def test_scan_models_basic(self):
-        """Test basic model scanning"""
-        requester = litellmchat.LiteLLMRequester(
-            ap=Mock(),
-            config={
-                'base_url': 'https://api.openai.com/v1',
-                'timeout': 60,
-            },
-        )
-
-        # Mock httpx response
-        mock_response = Mock()
-        mock_response.json = Mock(
-            return_value={
-                'data': [
-                    {'id': 'gpt-4o'},
-                    {'id': 'text-embedding-3-small'},
-                    {'id': 'gpt-3.5-turbo'},
-                ]
-            }
-        )
-        mock_response.raise_for_status = Mock()
-
-        with patch('httpx.AsyncClient') as mock_client:
-            mock_client.return_value.__aenter__ = AsyncMock(return_value=Mock())
-            mock_client.return_value.__aenter__.return_value.get = AsyncMock(return_value=mock_response)
-
-            result = await requester.scan_models(api_key='test-key')
-
-            assert 'models' in result
-            assert len(result['models']) == 3
-            # Check LLM models are first
-            assert result['models'][0]['type'] == 'llm'
-            # Check embedding model is detected
-            embedding_models = [m for m in result['models'] if m['type'] == 'embedding']
-            assert len(embedding_models) == 1
-
-    @pytest.mark.asyncio
-    async def test_scan_models_no_base_url(self):
-        """Test scan_models without base_url raises error"""
-        requester = litellmchat.LiteLLMRequester(
-            ap=Mock(),
-            config={
-                'base_url': '',
-            },
-        )
-
-        with pytest.raises(errors.RequesterError) as exc_info:
-            await requester.scan_models()
-
-        assert 'Base URL required' in str(exc_info.value)
-
-
-if __name__ == '__main__':
-    pytest.main([__file__, '-v'])

web/src/app/home/plugins/components/plugin-installed/PluginCardVO.ts

@@ -14,6 +14,7 @@ export interface IPluginCardVO {
   components: PluginComponent[];
   debug: boolean;
   hasUpdate?: boolean;
+  type?: 'plugin' | 'mcp' | 'skill';
 }
 
 export class PluginCardVO implements IPluginCardVO {
@@ -30,6 +31,7 @@ export class PluginCardVO implements IPluginCardVO {
   status: string;
   components: PluginComponent[];
   hasUpdate?: boolean;
+  type?: 'plugin' | 'mcp' | 'skill';
 
   constructor(prop: IPluginCardVO) {
     this.author = prop.author;
@@ -45,5 +47,6 @@ export class PluginCardVO implements IPluginCardVO {
     this.install_source = prop.install_source;
     this.install_info = prop.install_info;
     this.hasUpdate = prop.hasUpdate;
+    this.type = prop.type;
   }
 }

web/src/app/home/plugins/components/plugin-installed/PluginInstalledComponent.tsx

@@ -88,6 +88,8 @@ const PluginInstalledComponent = forwardRef<PluginInstalledComponentRef>(
 
         // 转换并比较版本号
         const pluginCards = installedPlugins.map((plugin) => {
+          const marketplaceKey = `${plugin.manifest.manifest.metadata.author}/${plugin.manifest.manifest.metadata.name}`;
+          const marketplacePlugin = marketplacePluginMap.get(marketplaceKey);
           const cardVO = new PluginCardVO({
             author: plugin.manifest.manifest.metadata.author ?? '',
             label: extractI18nObject(plugin.manifest.manifest.metadata.label),
@@ -106,13 +108,12 @@ const PluginInstalledComponent = forwardRef<PluginInstalledComponentRef>(
             priority: plugin.priority,
             install_source: plugin.install_source,
             install_info: plugin.install_info,
+            type: marketplacePlugin?.type,
           });
 
           // 检查是否来自市场且有更新
-          if (cardVO.install_source === 'marketplace') {
-            const marketplaceKey = `${cardVO.author}/${cardVO.name}`;
-            const marketplacePlugin = marketplacePluginMap.get(marketplaceKey);
-            if (marketplacePlugin && marketplacePlugin.latest_version) {
+          if (cardVO.install_source === 'marketplace' && marketplacePlugin) {
+            if (marketplacePlugin.latest_version) {
               cardVO.hasUpdate = isNewerVersion(
                 marketplacePlugin.latest_version,
                 cardVO.version,

web/src/app/home/plugins/components/plugin-installed/plugin-card/PluginCardComponent.tsx

@@ -60,6 +60,24 @@ export default function PluginCardComponent({
                   >
                     v{cardVO.version}
                   </Badge>
+                  {cardVO.type && (
+                    <Badge
+                      variant="outline"
+                      className={`text-[0.7rem] flex-shrink-0 ${
+                        cardVO.type === 'mcp'
+                          ? 'border-sky-500 text-sky-600 dark:border-sky-400 dark:text-sky-300'
+                          : cardVO.type === 'skill'
+                          ? 'border-emerald-500 text-emerald-600 dark:border-emerald-400 dark:text-emerald-300'
+                          : 'border-violet-500 text-violet-600 dark:border-violet-400 dark:text-violet-300'
+                      }`}
+                    >
+                      {cardVO.type === 'mcp'
+                        ? 'MCP'
+                        : cardVO.type === 'skill'
+                        ? t('common.skill')
+                        : t('market.typePlugin')}
+                    </Badge>
+                  )}
                   {cardVO.debug && (
                     <Badge
                       variant="outline"

web/src/app/home/plugins/components/plugin-market/PluginComponentList.tsx

@@ -0,0 +1,77 @@
+import { Fragment } from 'react';
+import { TFunction } from 'i18next';
+import { Wrench, AudioWaveform, Hash, Book, FileText } from 'lucide-react';
+import { Badge } from '@/components/ui/badge';
+
+export default function PluginComponentList({
+  components,
+  showComponentName,
+  showTitle,
+  useBadge,
+  t,
+  responsive = false,
+}: {
+  components: Record<string, number>;
+  showComponentName: boolean;
+  showTitle: boolean;
+  useBadge: boolean;
+  t: TFunction;
+  responsive?: boolean;
+}) {
+  const kindIconMap: Record<string, React.ReactNode> = {
+    Tool: <Wrench className="w-5 h-5" />,
+    EventListener: <AudioWaveform className="w-5 h-5" />,
+    Command: <Hash className="w-5 h-5" />,
+    KnowledgeEngine: <Book className="w-5 h-5" />,
+    Parser: <FileText className="w-5 h-5" />,
+  };
+
+  const componentKindList = Object.keys(components || {});
+
+  return (
+    <>
+      {showTitle && <div>{t('market.componentsList')}</div>}
+      {componentKindList.length > 0 && (
+        <>
+          {componentKindList.map((kind) => {
+            return (
+              <Fragment key={kind}>
+                {useBadge && (
+                  <Badge variant="outline" className="flex items-center gap-1">
+                    {kindIconMap[kind]}
+                    {responsive ? (
+                      <span className="hidden md:inline">
+                        {t('market.componentName.' + kind)}
+                      </span>
+                    ) : (
+                      showComponentName && t('market.componentName.' + kind)
+                    )}
+                    <span className="ml-1">{components[kind]}</span>
+                  </Badge>
+                )}
+
+                {!useBadge && (
+                  <div
+                    className="flex flex-row items-center justify-start gap-[0.2rem]"
+                  >
+                    {kindIconMap[kind]}
+                    {responsive ? (
+                      <span className="hidden md:inline">
+                        {t('market.componentName.' + kind)}
+                      </span>
+                    ) : (
+                      showComponentName && t('market.componentName.' + kind)
+                    )}
+                    <span className="ml-1">{components[kind]}</span>
+                  </div>
+                )}
+              </Fragment>
+            );
+          })}
+        </>
+      )}
+
+      {componentKindList.length === 0 && <div>{t('market.noComponents')}</div>}
+    </>
+  );
+}

web/src/app/home/plugins/components/plugin-market/PluginMarketComponent.tsx

@@ -8,14 +8,23 @@ import {
   SelectTrigger,
   SelectValue,
 } from '@/components/ui/select';
-import { ToggleGroup, ToggleGroupItem } from '@/components/ui/toggle-group';
+import {
+  Popover,
+  PopoverContent,
+  PopoverTrigger,
+} from '@/components/ui/popover';
+import { Separator } from '@/components/ui/separator';
+import {
+  ToggleGroup,
+  ToggleGroupItem,
+} from '@/components/ui/toggle-group';
 import {
   Search,
   Wrench,
   AudioWaveform,
-  Hash,
   Book,
-  FileText,
+  SlidersHorizontal,
+  X,
 } from 'lucide-react';
 import PluginMarketCardComponent from './plugin-market-card/PluginMarketCardComponent';
 import { PluginMarketCardVO } from './plugin-market-card/PluginMarketCardVO';
@@ -26,6 +35,7 @@ import { extractI18nObject } from '@/i18n/I18nProvider';
 import { toast } from 'sonner';
 import { ApiRespMarketplacePlugins } from '@/app/infra/entities/api';
 import { LoadingSpinner } from '@/components/ui/loading-spinner';
+import { Button } from '@/components/ui/button';
 import { TagsFilter } from './TagsFilter';
 import { PluginTag } from '@/app/infra/http/CloudServiceClient';
 
@@ -55,6 +65,15 @@ function MarketPageContent({
     'Parser',
   ];
 
+  const validTypes = ['plugin', 'mcp', 'skill'];
+
+  const extensionTypeOptions = [
+    { value: 'all', label: t('market.filters.allFormats'), icon: null },
+    { value: 'plugin', label: t('market.typePlugin'), icon: Wrench },
+    { value: 'mcp', label: t('market.typeMCP'), icon: AudioWaveform },
+    { value: 'skill', label: t('market.typeSkill'), icon: Book },
+  ];
+
   const [searchQuery, setSearchQuery] = useState('');
   const [componentFilter, setComponentFilter] = useState<string>(() => {
     const category = searchParams.get('category');
@@ -63,6 +82,14 @@ function MarketPageContent({
     }
     return 'all';
   });
+  const [typeFilter, setTypeFilter] = useState<string>(() => {
+    const type = searchParams.get('type');
+    if (type && validTypes.includes(type)) {
+      return type;
+    }
+    return 'all';
+  });
+  const activeAdvancedFilters = typeFilter === 'all' ? 0 : 1;
   const [selectedTags, setSelectedTags] = useState<string[]>([]);
   const [availableTags, setAvailableTags] = useState<PluginTag[]>([]);
   const [tagNames, setTagNames] = useState<Record<string, string>>({});
@@ -136,9 +163,44 @@ function MarketPageContent({
       version: plugin.latest_version,
       components: plugin.components,
       tags: plugin.tags || [],
+      type: plugin.type,
     });
   }, []);
 
+  const transformMCPToVO = useCallback((mcp: any): PluginMarketCardVO => {
+    return new PluginMarketCardVO({
+      pluginId: mcp.author + ' / ' + mcp.name,
+      author: mcp.author,
+      pluginName: mcp.name,
+      label: extractI18nObject(mcp.label),
+      description: extractI18nObject(mcp.description) || t('market.noDescription'),
+      installCount: mcp.install_count || 0,
+      iconURL: mcp.icon || getCloudServiceClientSync().getPluginIconURL(mcp.author, mcp.name),
+      githubURL: mcp.repository,
+      version: mcp.latest_version,
+      components: mcp.components || {},
+      tags: mcp.tags || [],
+      type: 'mcp',
+    });
+  }, [t]);
+
+  const transformSkillToVO = useCallback((skill: any): PluginMarketCardVO => {
+    return new PluginMarketCardVO({
+      pluginId: skill.author + ' / ' + skill.name,
+      author: skill.author,
+      pluginName: skill.name,
+      label: extractI18nObject(skill.label),
+      description: extractI18nObject(skill.description) || t('market.noDescription'),
+      installCount: skill.install_count || 0,
+      iconURL: skill.icon || getCloudServiceClientSync().getPluginIconURL(skill.author, skill.name),
+      githubURL: skill.repository,
+      version: skill.latest_version,
+      components: skill.components || {},
+      tags: skill.tags || [],
+      type: 'skill',
+    });
+  }, [t]);
+
   // 获取插件列表
   const fetchPlugins = useCallback(
     async (page: number, isSearch: boolean = false, reset: boolean = false) => {
@@ -152,30 +214,98 @@ function MarketPageContent({
         const { sortBy, sortOrder } = getCurrentSort();
         const filterValue =
           componentFilter === 'all' ? undefined : componentFilter;
+        const query = isSearch && searchQuery.trim() ? searchQuery.trim() : '';
 
-        // Always use searchMarketplacePlugins to support component filtering and tags filtering
-        const response =
-          await getCloudServiceClientSync().searchMarketplacePlugins(
-            isSearch && searchQuery.trim() ? searchQuery.trim() : '',
+        let newPlugins: PluginMarketCardVO[] = [];
+        let total = 0;
+
+        if (typeFilter === 'all') {
+          let pluginsResult: PluginMarketCardVO[] = [];
+          let mcpsResult: PluginMarketCardVO[] = [];
+          let skillsResult: PluginMarketCardVO[] = [];
+          let pluginsTotal = 0;
+          let mcpsTotal = 0;
+          let skillsTotal = 0;
+
+          try {
+            const pluginsResponse = await getCloudServiceClientSync().searchMarketplacePlugins(
+              query,
+              page,
+              pageSize,
+              sortBy,
+              sortOrder,
+              filterValue,
+              selectedTags.length > 0 ? selectedTags : undefined,
+              'plugin',
+            );
+            pluginsResult = pluginsResponse.plugins
+              .filter((plugin) => {
+                const keys = Object.keys(plugin.components || {});
+                return !(keys.length > 0 && keys.every((k) => k === 'KnowledgeRetriever'));
+              })
+              .map(transformToVO);
+            pluginsTotal = pluginsResponse.total || 0;
+          } catch (e) {
+            console.warn('Failed to fetch plugins:', e);
+          }
+
+          try {
+            const mcpsResponse = await getCloudServiceClientSync().searchMarketplacePlugins(
+              query,
+              page,
+              pageSize,
+              sortBy,
+              sortOrder,
+              filterValue,
+              selectedTags.length > 0 ? selectedTags : undefined,
+              'mcp',
+            );
+            mcpsResult = (mcpsResponse.plugins || []).map(transformMCPToVO);
+            mcpsTotal = mcpsResponse.total || 0;
+          } catch (e) {
+            console.warn('Failed to fetch mcps:', e);
+          }
+
+          try {
+            const skillsResponse = await getCloudServiceClientSync().searchMarketplacePlugins(
+              query,
+              page,
+              pageSize,
+              sortBy,
+              sortOrder,
+              filterValue,
+              selectedTags.length > 0 ? selectedTags : undefined,
+              'skill',
+            );
+            skillsResult = (skillsResponse.plugins || []).map(transformSkillToVO);
+            skillsTotal = skillsResponse.total || 0;
+          } catch (e) {
+            console.warn('Failed to fetch skills:', e);
+          }
+
+          newPlugins = [...pluginsResult, ...mcpsResult, ...skillsResult];
+          total = pluginsTotal + mcpsTotal + skillsTotal;
+        } else {
+          const response = await getCloudServiceClientSync().searchMarketplacePlugins(
+            query,
             page,
             pageSize,
             sortBy,
             sortOrder,
             filterValue,
             selectedTags.length > 0 ? selectedTags : undefined,
+            typeFilter === 'all' ? undefined : typeFilter,
           );
 
-        const data: ApiRespMarketplacePlugins = response;
-        const newPlugins = data.plugins
-          .filter((plugin) => {
-            // Hide plugins that only contain deprecated KnowledgeRetriever components
-            const keys = Object.keys(plugin.components || {});
-            return !(
-              keys.length > 0 && keys.every((k) => k === 'KnowledgeRetriever')
-            );
-          })
-          .map(transformToVO);
-        const total = data.total;
+          const data: ApiRespMarketplacePlugins = response;
+          newPlugins = data.plugins
+            .filter((plugin) => {
+              const keys = Object.keys(plugin.components || {});
+              return !(keys.length > 0 && keys.every((k) => k === 'KnowledgeRetriever'));
+            })
+            .map(transformToVO);
+          total = data.total;
+        }
 
         if (reset || page === 1) {
           setPlugins(newPlugins);
@@ -185,8 +315,8 @@ function MarketPageContent({
 
         setTotal(total);
         setHasMore(
-          data.plugins.length === pageSize &&
-            plugins.length + newPlugins.length < total,
+          newPlugins.length > 0 &&
+            (reset || page === 1 ? newPlugins.length : plugins.length + newPlugins.length) < total,
         );
       } catch (error) {
         console.error('Failed to fetch plugins:', error);
@@ -202,8 +332,11 @@ function MarketPageContent({
       selectedTags,
       pageSize,
       transformToVO,
+      transformMCPToVO,
+      transformSkillToVO,
       plugins.length,
       getCurrentSort,
+      typeFilter,
     ],
   );
 
@@ -313,10 +446,29 @@ function MarketPageContent({
     // fetchPlugins will be called by useEffect when componentFilter changes
   }, []);
 
+  // Handle type filter change
+  const handleTypeFilterChange = useCallback((value: string) => {
+    setTypeFilter(value);
+    setCurrentPage(1);
+    setPlugins([]);
+
+    // Update URL query param to keep it in sync
+    const params = new URLSearchParams(window.location.search);
+    if (value === 'all') {
+      params.delete('type');
+    } else {
+      params.set('type', value);
+    }
+    const newUrl = params.toString()
+      ? `${window.location.pathname}?${params.toString()}`
+      : window.location.pathname;
+    window.history.replaceState({}, '', newUrl);
+  }, []);
+
   // 当排序选项或组件筛选变化时重新加载数据
   useEffect(() => {
     fetchPlugins(1, !!searchQuery.trim(), true);
-  }, [sortOption, componentFilter]);
+  }, [sortOption, componentFilter, typeFilter]);
 
   // Tags 筛选变化时重新搜索
   useEffect(() => {
@@ -429,9 +581,9 @@ function MarketPageContent({
     <div className="h-full flex flex-col">
       {/* Fixed header with search and sort controls */}
       <div className="flex-shrink-0 space-y-4 px-3 sm:px-4 py-4 sm:py-6">
-        {/* Search box and Tags filter */}
-        <div className="flex flex-col sm:flex-row items-center justify-center gap-3">
-          <div className="relative w-full max-w-2xl">
+        {/* Search box */}
+        <div className="flex flex-col lg:flex-row items-stretch lg:items-center justify-center gap-3">
+          <div className="relative w-full lg:max-w-xl">
             <Search className="absolute left-3 top-1/2 transform -translate-y-1/2 text-muted-foreground h-4 w-4" />
             <Input
               placeholder={t('market.searchPlaceholder')}
@@ -446,7 +598,6 @@ function MarketPageContent({
               }}
               onKeyPress={(e) => {
                 if (e.key === 'Enter') {
-                  // Immediately search, clear debounce timer
                   if (searchTimeoutRef.current) {
                     clearTimeout(searchTimeoutRef.current);
                   }
@@ -457,90 +608,9 @@ function MarketPageContent({
             />
           </div>
 
-          {/* Tags filter */}
-          <TagsFilter
-            availableTags={availableTags}
-            selectedTags={selectedTags}
-            onTagsChange={handleTagsChange}
-          />
-        </div>
-
-        {/* Component filter and sort */}
-        <div className="flex flex-col sm:flex-row items-center justify-center gap-3 sm:gap-4 px-3 sm:px-4">
-          {/* Component filter */}
-          <div className="flex flex-col sm:flex-row items-center gap-2 min-w-0 max-w-full">
-            <span className="text-xs sm:text-sm text-muted-foreground whitespace-nowrap">
-              {t('market.filterByComponent')}:
-            </span>
-            <div className="overflow-x-auto max-w-full [&::-webkit-scrollbar]:hidden [-ms-overflow-style:none] [scrollbar-width:none]">
-              <ToggleGroup
-                type="single"
-                spacing={2}
-                size="sm"
-                value={componentFilter}
-                onValueChange={(value) => {
-                  if (value) handleComponentFilterChange(value);
-                }}
-                className="justify-start flex-nowrap"
-              >
-                <ToggleGroupItem
-                  value="all"
-                  aria-label="All components"
-                  className="text-xs sm:text-sm cursor-pointer"
-                >
-                  {t('market.allComponents')}
-                </ToggleGroupItem>
-                <ToggleGroupItem
-                  value="Tool"
-                  aria-label="Tool"
-                  className="text-xs sm:text-sm cursor-pointer"
-                >
-                  <Wrench className="h-4 w-4 mr-1" />
-                  {t('plugins.componentName.Tool')}
-                </ToggleGroupItem>
-                <ToggleGroupItem
-                  value="Command"
-                  aria-label="Command"
-                  className="text-xs sm:text-sm cursor-pointer"
-                >
-                  <Hash className="h-4 w-4 mr-1" />
-                  {t('plugins.componentName.Command')}
-                </ToggleGroupItem>
-                <ToggleGroupItem
-                  value="EventListener"
-                  aria-label="EventListener"
-                  className="text-xs sm:text-sm cursor-pointer"
-                >
-                  <AudioWaveform className="h-4 w-4 mr-1" />
-                  {t('plugins.componentName.EventListener')}
-                </ToggleGroupItem>
-                <ToggleGroupItem
-                  value="KnowledgeEngine"
-                  aria-label="KnowledgeEngine"
-                  className="text-xs sm:text-sm cursor-pointer"
-                >
-                  <Book className="h-4 w-4 mr-1" />
-                  {t('plugins.componentName.KnowledgeEngine')}
-                </ToggleGroupItem>
-                <ToggleGroupItem
-                  value="Parser"
-                  aria-label="Parser"
-                  className="text-xs sm:text-sm cursor-pointer"
-                >
-                  <FileText className="h-4 w-4 mr-1" />
-                  {t('plugins.componentName.Parser')}
-                </ToggleGroupItem>
-              </ToggleGroup>
-            </div>
-          </div>
-
-          {/* Sort dropdown */}
-          <div className="flex items-center gap-2 sm:gap-3">
-            <span className="text-xs sm:text-sm text-muted-foreground whitespace-nowrap">
-              {t('market.sortBy')}:
-            </span>
+          <div className="flex w-full items-center justify-end gap-2 lg:w-auto">
             <Select value={sortOption} onValueChange={handleSortChange}>
-              <SelectTrigger className="w-40 sm:w-48 text-xs sm:text-sm">
+              <SelectTrigger className="w-[128px] sm:w-40 text-xs sm:text-sm">
                 <SelectValue />
               </SelectTrigger>
               <SelectContent>
@@ -551,9 +621,96 @@ function MarketPageContent({
                 ))}
               </SelectContent>
             </Select>
+
+            <Popover>
+              <PopoverTrigger asChild>
+                <Button variant="outline" className="relative">
+                  <SlidersHorizontal className="h-4 w-4" />
+                  <span className="hidden sm:inline">{t('market.filters.more')}</span>
+                  {activeAdvancedFilters > 0 && (
+                    <span className="absolute -right-1 -top-1 flex h-4 min-w-4 items-center justify-center rounded-full bg-primary px-1 text-[10px] leading-none text-primary-foreground">
+                      {activeAdvancedFilters}
+                    </span>
+                  )}
+                </Button>
+              </PopoverTrigger>
+              <PopoverContent align="end" className="w-[320px] space-y-4">
+                <div>
+                  <div className="text-sm font-medium">{t('market.filters.advancedTitle')}</div>
+                  <div className="mt-1 text-xs text-muted-foreground">
+                    {t('market.filters.advancedDescription')}
+                  </div>
+                </div>
+                <Separator />
+                <div className="space-y-2">
+                  <div className="text-xs font-medium text-muted-foreground">
+                    {t('market.filters.technicalType')}
+                  </div>
+                  <ToggleGroup
+                    type="single"
+                    spacing={2}
+                    size="sm"
+                    value={typeFilter}
+                    onValueChange={(value) => {
+                      if (value) handleTypeFilterChange(value);
+                    }}
+                    className="flex flex-wrap justify-start gap-2"
+                  >
+                    {extensionTypeOptions.map((option) => {
+                      const Icon = option.icon;
+                      return (
+                        <ToggleGroupItem
+                          key={option.value}
+                          value={option.value}
+                          aria-label={option.label}
+                          className="cursor-pointer text-xs"
+                        >
+                          {Icon && <Icon className="mr-1 h-3.5 w-3.5" />}
+                          {option.label}
+                        </ToggleGroupItem>
+                      );
+                    })}
+                  </ToggleGroup>
+                </div>
+              </PopoverContent>
+            </Popover>
           </div>
         </div>
 
+        {/* Quick tag filter buttons */}
+        <div className="mx-auto flex w-full max-w-4xl items-center gap-2 overflow-x-auto pb-1 sm:flex-wrap sm:justify-center sm:overflow-visible">
+          <Button
+            type="button"
+            variant={selectedTags.length === 0 ? 'secondary' : 'ghost'}
+            size="sm"
+            className="h-8 shrink-0"
+            onClick={() => handleTagsChange([])}
+          >
+            {t('market.allExtensions')}
+          </Button>
+          {availableTags.map((tag) => {
+            const selected = selectedTags.includes(tag.tag);
+            return (
+              <Button
+                key={tag.tag}
+                type="button"
+                variant={selected ? 'secondary' : 'ghost'}
+                size="sm"
+                className="h-8 shrink-0"
+                onClick={() => {
+                  const newTags = selected
+                    ? selectedTags.filter((t) => t !== tag.tag)
+                    : [...selectedTags, tag.tag];
+                  handleTagsChange(newTags);
+                }}
+              >
+                {tagNames[tag.tag] || tag.tag}
+                {selected && <X className="h-3.5 w-3.5" />}
+              </Button>
+            );
+          })}
+        </div>
+
         {/* Search results stats */}
         {total > 0 && (
           <div className="text-center text-muted-foreground text-sm">

web/src/app/home/plugins/components/plugin-market/RecommendationLists.tsx

@@ -38,6 +38,7 @@ function pluginToVO(
     version: plugin.latest_version,
     components: plugin.components,
     tags: plugin.tags || [],
+    type: plugin.type,
   });
 }
 

web/src/app/home/plugins/components/plugin-market/plugin-market-card/PluginMarketCardComponent.tsx

@@ -1,17 +1,15 @@
 import { PluginMarketCardVO } from './PluginMarketCardVO';
+import { useRef, useState, useEffect } from 'react';
 import { useTranslation } from 'react-i18next';
+import PluginComponentList from '../PluginComponentList';
 import { Badge } from '@/components/ui/badge';
+import { Info, Package } from 'lucide-react';
 import {
-  Wrench,
-  AudioWaveform,
-  Hash,
-  Download,
-  ExternalLink,
-  Book,
-  FileText,
-} from 'lucide-react';
-import { useState, useRef, useEffect } from 'react';
-import { Button } from '@/components/ui/button';
+  Tooltip,
+  TooltipContent,
+  TooltipProvider,
+  TooltipTrigger,
+} from '@/components/ui/tooltip';
 
 export default function PluginMarketCardComponent({
   cardVO,
@@ -23,11 +21,24 @@ export default function PluginMarketCardComponent({
   tagNames?: Record<string, string>;
 }) {
   const { t } = useTranslation();
-  const [isHovered, setIsHovered] = useState(false);
   const bottomRef = useRef<HTMLDivElement>(null);
   const [visibleTags, setVisibleTags] = useState(2);
+  const [iconFailed, setIconFailed] = useState(!cardVO.iconURL);
+
+  const pluginDetailUrl = `https://space.langbot.app/market/${cardVO.author}/${cardVO.pluginName}`;
+
+  const isDeprecated = (() => {
+    if (!cardVO.components) return false;
+    const keys = Object.keys(cardVO.components);
+    return keys.length > 0 && keys.every((k) => k === 'KnowledgeRetriever');
+  })();
+
+  const showTypeBadge = cardVO.type;
+
+  useEffect(() => {
+    setIconFailed(!cardVO.iconURL);
+  }, [cardVO.iconURL]);
 
-  // Measure how many tags fit in the bottom row
   useEffect(() => {
     const tags = cardVO.tags;
     if (!bottomRef.current || !tags || tags.length === 0) return;
@@ -43,10 +54,7 @@ export default function PluginMarketCardComponent({
       }
       const tagWidth = 80;
       const plusBadgeWidth = 40;
-      const maxTags = Math.max(
-        0,
-        Math.floor((availableForTags - plusBadgeWidth) / tagWidth),
-      );
+      const maxTags = Math.max(0, Math.floor((availableForTags - plusBadgeWidth) / tagWidth));
       if (maxTags >= tags.length) {
         setVisibleTags(tags.length);
       } else {
@@ -62,51 +70,72 @@ export default function PluginMarketCardComponent({
 
   const remainingTags = cardVO.tags ? cardVO.tags.length - visibleTags : 0;
 
-  function handleInstallClick(e: React.MouseEvent) {
-    e.stopPropagation();
-    if (onInstall) {
-      onInstall(cardVO.author, cardVO.pluginName);
-    }
-  }
-
-  function handleViewDetailsClick(e: React.MouseEvent) {
-    e.stopPropagation();
-    const detailUrl = `https://space.langbot.app/market/${cardVO.author}/${cardVO.pluginName}`;
-    window.open(detailUrl, '_blank');
-  }
-
-  const kindIconMap: Record<string, React.ReactNode> = {
-    Tool: <Wrench className="w-4 h-4" />,
-    EventListener: <AudioWaveform className="w-4 h-4" />,
-    Command: <Hash className="w-4 h-4" />,
-    KnowledgeEngine: <Book className="w-4 h-4" />,
-    Parser: <FileText className="w-4 h-4" />,
-  };
-
   return (
-    <div
-      className="w-[100%] h-auto min-h-[8rem] sm:min-h-[9rem] bg-white rounded-[10px] border border-[#e4e4e7] dark:border-[#27272a] p-3 sm:p-[1rem] hover:border-[#a1a1aa] dark:hover:border-[#3f3f46] transition-all duration-200 dark:bg-[#1f1f22] relative"
-      onMouseEnter={() => setIsHovered(true)}
-      onMouseLeave={() => setIsHovered(false)}
+    <a
+      href={pluginDetailUrl}
+      target="_blank"
+      rel="noopener noreferrer"
+      className="w-[100%] h-[10rem] bg-white rounded-[10px] shadow-[0px_0px_4px_0_rgba(0,0,0,0.2)] p-3 sm:p-[1rem] cursor-pointer hover:shadow-[0px_2px_8px_0_rgba(0,0,0,0.15)] transition-shadow duration-200 dark:bg-[#1f1f22] dark:shadow-[0px_0px_4px_0_rgba(255,255,255,0.1)] dark:hover:shadow-[0px_2px_8px_0_rgba(255,255,255,0.15)] block"
     >
-      <div className="w-full h-full flex flex-col justify-between gap-3">
-        {/* 上部分：插件信息 */}
-        <div className="flex flex-row items-start justify-start gap-2 sm:gap-[1.2rem] min-h-0">
-          <img
-            src={cardVO.iconURL}
-            alt="plugin icon"
-            className="w-12 h-12 sm:w-16 sm:h-16 flex-shrink-0 rounded-[8%]"
-          />
+      <div className="w-full h-full flex flex-col justify-between">
+        <div className="flex flex-row items-start justify-start gap-2 sm:gap-[1.2rem] min-h-0 flex-1 overflow-hidden">
+          {iconFailed ? (
+            <div className="w-12 h-12 sm:w-16 sm:h-16 flex-shrink-0 rounded-[8%] border bg-muted text-muted-foreground flex items-center justify-center">
+              <Package className="w-6 h-6 sm:w-8 sm:h-8" />
+            </div>
+          ) : (
+            <img
+              src={cardVO.iconURL}
+              alt="plugin icon"
+              className="w-12 h-12 sm:w-16 sm:h-16 flex-shrink-0 rounded-[8%] object-cover"
+              loading="lazy"
+              decoding="async"
+              fetchPriority="low"
+              onError={() => setIconFailed(true)}
+            />
+          )}
 
           <div className="flex-1 flex flex-col items-start justify-start gap-[0.4rem] sm:gap-[0.6rem] min-w-0 overflow-hidden">
             <div className="flex flex-col items-start justify-start w-full min-w-0">
-              <div className="text-[0.65rem] sm:text-[0.7rem] text-[#666] dark:text-[#999] truncate w-full">
-                {cardVO.pluginId}
-              </div>
+              <div className="text-[0.65rem] sm:text-[0.7rem] text-[#666] dark:text-[#999] truncate w-full">{cardVO.pluginId}</div>
               <div className="flex items-center gap-1.5 w-full min-w-0">
-                <div className="text-base sm:text-[1.2rem] text-black dark:text-[#f0f0f0] truncate">
-                  {cardVO.label}
-                </div>
+                <div className="text-base sm:text-[1.2rem] text-black dark:text-[#f0f0f0] truncate">{cardVO.label}</div>
+                {isDeprecated && (
+                  <TooltipProvider delayDuration={200}>
+                    <Tooltip>
+                      <TooltipTrigger asChild onClick={(e) => e.preventDefault()}>
+                        <Badge
+                          variant="outline"
+                          className="text-[0.6rem] px-1.5 py-0 h-4 flex-shrink-0 border-red-400 text-red-500 dark:border-red-500 dark:text-red-400 gap-0.5 cursor-help"
+                        >
+                          {t('market.deprecated')}
+                          <Info className="w-2.5 h-2.5" />
+                        </Badge>
+                      </TooltipTrigger>
+                      <TooltipContent side="top" className="max-w-[240px] text-xs">
+                        {t('market.deprecatedTooltip')}
+                      </TooltipContent>
+                    </Tooltip>
+                  </TooltipProvider>
+                )}
+                {showTypeBadge && (
+                  <Badge
+                    variant="outline"
+                    className={`text-[0.6rem] px-1.5 py-0 h-4 flex-shrink-0 gap-0.5 ${
+                      cardVO.type === 'mcp'
+                        ? 'border-sky-500 text-sky-600 dark:border-sky-400 dark:text-sky-300'
+                        : cardVO.type === 'skill'
+                        ? 'border-emerald-500 text-emerald-600 dark:border-emerald-400 dark:text-emerald-300'
+                        : 'border-violet-500 text-violet-600 dark:border-violet-400 dark:text-violet-300'
+                    }`}
+                  >
+                    {cardVO.type === 'mcp'
+                      ? 'MCP'
+                      : cardVO.type === 'skill'
+                      ? t('common.skill')
+                      : t('market.typePlugin')}
+                  </Badge>
+                )}
               </div>
             </div>
 
@@ -118,11 +147,12 @@ export default function PluginMarketCardComponent({
           <div className="flex flex-row items-start justify-center gap-[0.4rem] flex-shrink-0">
             {cardVO.githubURL && (
               <svg
-                className="w-5 h-5 sm:w-[1.4rem] sm:h-[1.4rem] text-black cursor-pointer hover:text-gray-600 dark:text-[#f0f0f0] flex-shrink-0"
+                className="w-5 h-5 sm:w-[1.4rem] sm:h-[1.4rem] text-black cursor-pointer hover:text-gray-600 dark:text-[#f0f0f0] dark:hover:text-[#c0c0c0] flex-shrink-0"
                 xmlns="http://www.w3.org/2000/svg"
                 viewBox="0 0 24 24"
                 fill="currentColor"
                 onClick={(e) => {
+                  e.preventDefault();
                   e.stopPropagation();
                   window.open(cardVO.githubURL, '_blank');
                 }}
@@ -133,13 +163,8 @@ export default function PluginMarketCardComponent({
           </div>
         </div>
 
-        {/* 下部分：下载量、标签和组件列表 */}
-        <div
-          ref={bottomRef}
-          className="w-full flex flex-row items-center justify-between gap-2 px-0 sm:px-[0.4rem] flex-shrink-0 overflow-hidden"
-        >
+        <div ref={bottomRef} className="w-full flex flex-row items-center justify-between gap-2 px-0 sm:px-[0.4rem] flex-shrink-0 overflow-hidden">
           <div className="flex flex-row items-center justify-start gap-2 min-w-0 overflow-hidden">
-            {/* 下载数量 */}
             <div className="flex flex-row items-center gap-[0.3rem] sm:gap-[0.4rem] flex-shrink-0">
               <svg
                 className="w-4 h-4 sm:w-[1.2rem] sm:h-[1.2rem] text-[#2563eb] dark:text-[#5b8def] flex-shrink-0"
@@ -158,7 +183,6 @@ export default function PluginMarketCardComponent({
               </div>
             </div>
 
-            {/* Tags - adaptive */}
             {cardVO.tags && cardVO.tags.length > 0 && visibleTags > 0 && (
               <div className="flex flex-row items-center gap-1.5 overflow-hidden flex-shrink min-w-0">
                 {cardVO.tags.slice(0, visibleTags).map((tag) => (
@@ -180,9 +204,7 @@ export default function PluginMarketCardComponent({
                       <path d="M20.59 13.41l-7.17 7.17a2 2 0 0 1-2.83 0L2 12V2h10l8.59 8.59a2 2 0 0 1 0 2.82z" />
                       <line x1="7" y1="7" x2="7.01" y2="7" />
                     </svg>
-                    <span className="truncate max-w-[5rem]">
-                      {tagNames[tag] || tag}
-                    </span>
+                    <span className="truncate max-w-[5rem]">{tagNames[tag] || tag}</span>
                   </Badge>
                 ))}
                 {remainingTags > 0 && (
@@ -197,52 +219,20 @@ export default function PluginMarketCardComponent({
             )}
           </div>
 
-          {/* 组件列表 */}
           {cardVO.components && Object.keys(cardVO.components).length > 0 && (
-            <div className="flex flex-row items-center gap-1">
-              {Object.entries(cardVO.components).map(([kind, count]) => (
-                <Badge
-                  key={kind}
-                  variant="outline"
-                  className="flex items-center gap-1"
-                >
-                  {kindIconMap[kind]}
-                  <span className="ml-1">{count}</span>
-                </Badge>
-              ))}
+            <div className="flex flex-row items-center gap-1 flex-shrink-0">
+              <PluginComponentList
+                components={cardVO.components}
+                showComponentName={false}
+                showTitle={false}
+                useBadge={true}
+                t={t}
+                responsive={false}
+              />
             </div>
           )}
         </div>
       </div>
-
-      {/* Hover overlay with action buttons */}
-      <div
-        className={`absolute inset-0 bg-gray-100/55 dark:bg-black/35 rounded-[10px] flex items-center justify-center gap-3 transition-all duration-200 ${
-          isHovered ? 'opacity-100' : 'opacity-0 pointer-events-none'
-        }`}
-      >
-        <Button
-          onClick={handleInstallClick}
-          className={`bg-blue-600 hover:bg-blue-700 text-white px-4 py-2 rounded-lg shadow-sm flex items-center gap-2 transition-all duration-200 ${
-            isHovered ? 'translate-y-0 opacity-100' : 'translate-y-1 opacity-0'
-          }`}
-          style={{ transitionDelay: isHovered ? '10ms' : '0ms' }}
-        >
-          <Download className="w-4 h-4" />
-          {t('market.install')}
-        </Button>
-        <Button
-          onClick={handleViewDetailsClick}
-          variant="outline"
-          className={`bg-white hover:bg-gray-100 text-gray-900 dark:bg-white dark:hover:bg-gray-100 dark:text-gray-900 px-4 py-2 rounded-lg shadow-sm flex items-center gap-2 transition-all duration-200 ${
-            isHovered ? 'translate-y-0 opacity-100' : 'translate-y-1 opacity-0'
-          }`}
-          style={{ transitionDelay: isHovered ? '20ms' : '0ms' }}
-        >
-          <ExternalLink className="w-4 h-4" />
-          {t('market.viewDetails')}
-        </Button>
-      </div>
-    </div>
+    </a>
   );
-}
+}

web/src/app/home/plugins/components/plugin-market/plugin-market-card/PluginMarketCardVO.ts

@@ -10,6 +10,7 @@ export interface IPluginMarketCardVO {
   version: string;
   components?: Record<string, number>;
   tags?: string[];
+  type?: 'plugin' | 'mcp' | 'skill';
 }
 
 export class PluginMarketCardVO implements IPluginMarketCardVO {
@@ -24,6 +25,7 @@ export class PluginMarketCardVO implements IPluginMarketCardVO {
   version: string;
   components?: Record<string, number>;
   tags?: string[];
+  type?: 'plugin' | 'mcp' | 'skill';
 
   constructor(prop: IPluginMarketCardVO) {
     this.description = prop.description;
@@ -37,5 +39,6 @@ export class PluginMarketCardVO implements IPluginMarketCardVO {
     this.version = prop.version;
     this.components = prop.components;
     this.tags = prop.tags;
+    this.type = prop.type;
   }
 }

web/src/app/infra/entities/plugin/index.ts

@@ -42,6 +42,7 @@ export interface PluginV4 {
   latest_version: string;
   components: Record<string, number>;
   status: PluginV4Status;
+  type?: 'plugin' | 'mcp' | 'skill';
   created_at: string;
   updated_at: string;
 }

web/src/app/infra/http/CloudServiceClient.ts

@@ -38,7 +38,49 @@ export class CloudServiceClient extends BaseHttpClient {
     sort_order?: string,
     component_filter?: string,
     tags_filter?: string[],
+    type_filter?: string,
   ): Promise<ApiRespMarketplacePlugins> {
+    // Use different endpoints based on type_filter
+    if (type_filter === 'mcp') {
+      return this.post<{ mcps: PluginV4[]; total: number }>(
+        '/api/v1/marketplace/mcps/search',
+        {
+          query,
+          page,
+          page_size,
+          sort_by,
+          sort_order,
+          tags_filter,
+        },
+      ).then((resp) => ({
+        plugins: (resp?.mcps || []).map((mcp) => ({
+          ...mcp,
+          plugin_id: mcp.mcp_id || mcp.plugin_id,
+          type: 'mcp' as const,
+        })),
+        total: resp?.total || 0,
+      }));
+    } else if (type_filter === 'skill') {
+      return this.post<{ skills: PluginV4[]; total: number }>(
+        '/api/v1/marketplace/skills/search',
+        {
+          query,
+          page,
+          page_size,
+          sort_by,
+          sort_order,
+          tags_filter,
+        },
+      ).then((resp) => ({
+        plugins: (resp?.skills || []).map((skill) => ({
+          ...skill,
+          plugin_id: skill.skill_id || skill.plugin_id,
+          type: 'skill' as const,
+        })),
+        total: resp?.total || 0,
+      }));
+    }
+
     return this.post<ApiRespMarketplacePlugins>(
       '/api/v1/marketplace/plugins/search',
       {
@@ -49,6 +91,7 @@ export class CloudServiceClient extends BaseHttpClient {
         sort_order,
         component_filter,
         tags_filter,
+        type_filter,
       },
     );
   }

web/src/i18n/locales/en-US.ts

@@ -36,6 +36,7 @@ const enUS = {
     delete: 'Delete',
     add: 'Add',
     select: 'Select',
+    skill: 'Skill',
     cancel: 'Cancel',
     submit: 'Submit',
     error: 'Error',
@@ -617,11 +618,24 @@ const enUS = {
     markAsReadFailed: 'Mark as read failed',
     filterByComponent: 'Component',
     allComponents: 'All Components',
+    filterByType: 'Type',
+    allTypes: 'All Types',
+    typePlugin: 'Plugin',
+    typeMCP: 'MCP',
+    typeSkill: 'Skill',
     requestPlugin: 'Request Plugin',
     viewDetails: 'View Details',
     deprecated: 'Deprecated',
     deprecatedTooltip:
       'Please install the corresponding Knowledge Engine plugin.',
+    filters: {
+      allFormats: 'All Formats',
+      more: 'More',
+      advancedTitle: 'Advanced Filters',
+      advancedDescription: 'Filter by extension type',
+      technicalType: 'Technical Type',
+    },
+    allExtensions: 'All Extensions',
     tags: {
       filterByTags: 'Filter by Tags',
       selected: 'selected',

web/src/i18n/locales/es-ES.ts

@@ -38,6 +38,7 @@ const esES = {
     delete: 'Eliminar',
     add: 'Añadir',
     select: 'Seleccionar',
+    skill: 'Habilidad',
     cancel: 'Cancelar',
     submit: 'Enviar',
     error: 'Error',
@@ -630,11 +631,24 @@ const esES = {
     markAsReadFailed: 'Error al marcar como leído',
     filterByComponent: 'Componente',
     allComponents: 'Todos los componentes',
+    filterByType: 'Tipo',
+    allTypes: 'Todos los tipos',
+    typePlugin: 'Plugin',
+    typeMCP: 'MCP',
+    typeSkill: 'Habilidad',
     requestPlugin: 'Solicitar plugin',
     viewDetails: 'Ver detalles',
     deprecated: 'Obsoleto',
     deprecatedTooltip:
       'Por favor, instala el plugin de motor de conocimiento correspondiente.',
+    filters: {
+      allFormats: 'Todos los formatos',
+      more: 'Más',
+      advancedTitle: 'Filtros avanzados',
+      advancedDescription: 'Filtrar por tipo de extensión',
+      technicalType: 'Tipo técnico',
+    },
+    allExtensions: 'Todas las extensiones',
     tags: {
       filterByTags: 'Filtrar por etiquetas',
       selected: 'seleccionadas',

web/src/i18n/locales/ja-JP.ts

@@ -1,4 +1,4 @@
-const jaJP = {
+const jaJP = {
   sidebar: {
     home: 'ホーム',
     extensions: '拡張機能',
@@ -37,6 +37,7 @@
     delete: '削除',
     add: '追加',
     select: '選択してください',
+    skill: 'スキル',
     cancel: 'キャンセル',
     submit: '送信',
     error: 'エラー',
@@ -622,6 +623,11 @@
     markAsReadFailed: '既読に設定に失敗しました',
     filterByComponent: 'コンポーネント',
     allComponents: '全部コンポーネント',
+    filterByType: 'タイプ',
+    allTypes: '全部',
+    typePlugin: 'プラグイン',
+    typeMCP: 'MCP',
+    typeSkill: 'スキル',
     requestPlugin: 'プラグインをリクエスト',
     tags: {
       filterByTags: 'タグで絞り込み',
@@ -630,6 +636,14 @@
       clearAll: 'クリア',
       noTags: 'タグがありません',
     },
+    filters: {
+      allFormats: 'すべての形式',
+      more: 'もっと',
+      advancedTitle: '高度なフィルター',
+      advancedDescription: '拡張子タイプでフィルター',
+      technicalType: '技術タイプ',
+    },
+    allExtensions: 'すべての拡張機能',
     viewDetails: '詳細を表示',
     deprecated: '非推奨',
     deprecatedTooltip:

web/src/i18n/locales/ru-RU.ts

@@ -36,6 +36,7 @@ const ruRU = {
     delete: 'Удалить',
     add: 'Добавить',
     select: 'Выбрать',
+    skill: 'Навык',
     cancel: 'Отмена',
     submit: 'Отправить',
     error: 'Ошибка',
@@ -627,11 +628,24 @@ const ruRU = {
     markAsReadFailed: 'Не удалось отметить как прочитанное',
     filterByComponent: 'Компонент',
     allComponents: 'Все компоненты',
+    filterByType: 'Тип',
+    allTypes: 'Все типы',
+    typePlugin: 'Плагин',
+    typeMCP: 'MCP',
+    typeSkill: 'Навык',
     requestPlugin: 'Запросить плагин',
     viewDetails: 'Подробнее',
     deprecated: 'Устаревший',
     deprecatedTooltip:
       'Пожалуйста, установите соответствующий плагин движка знаний.',
+    filters: {
+      allFormats: 'Все форматы',
+      more: 'Ещё',
+      advancedTitle: 'Расширенные фильтры',
+      advancedDescription: 'Фильтр по типу расширения',
+      technicalType: 'Технический тип',
+    },
+    allExtensions: 'Все расширения',
     tags: {
       filterByTags: 'Фильтр по тегам',
       selected: 'выбрано',

web/src/i18n/locales/th-TH.ts

@@ -36,6 +36,7 @@ const thTH = {
     delete: 'ลบ',
     add: 'เพิ่ม',
     select: 'เลือก',
+    skill: 'สกิล',
     cancel: 'ยกเลิก',
     submit: 'ส่ง',
     error: 'ข้อผิดพลาด',
@@ -609,10 +610,23 @@ const thTH = {
     markAsReadFailed: 'ทำเครื่องหมายว่าอ่านแล้วล้มเหลว',
     filterByComponent: 'ส่วนประกอบ',
     allComponents: 'ส่วนประกอบทั้งหมด',
+    filterByType: 'ประเภท',
+    allTypes: 'ทุกประเภท',
+    typePlugin: 'ปลั๊กอิน',
+    typeMCP: 'MCP',
+    typeSkill: 'สกิล',
     requestPlugin: 'ขอปลั๊กอิน',
     viewDetails: 'ดูรายละเอียด',
     deprecated: 'เลิกใช้แล้ว',
     deprecatedTooltip: 'กรุณาติดตั้งปลั๊กอินเครื่องมือความรู้ที่เกี่ยวข้อง',
+    filters: {
+      allFormats: 'ทุกรูปแบบ',
+      more: 'เพิ่มเติม',
+      advancedTitle: 'ตัวกรองขั้นสูง',
+      advancedDescription: 'กรองตามประเภทส่วนขยาย',
+      technicalType: 'ประเภทเทคนิค',
+    },
+    allExtensions: 'ส่วนขยายทั้งหมด',
     tags: {
       filterByTags: 'กรองตามแท็ก',
       selected: 'เลือกแล้ว',

web/src/i18n/locales/vi-VN.ts

@@ -36,6 +36,7 @@ const viVN = {
     delete: 'Xóa',
     add: 'Thêm',
     select: 'Chọn',
+    skill: 'Kỹ năng',
     cancel: 'Hủy',
     submit: 'Gửi',
     error: 'Lỗi',
@@ -621,10 +622,23 @@ const viVN = {
     markAsReadFailed: 'Đánh dấu đã đọc thất bại',
     filterByComponent: 'Thành phần',
     allComponents: 'Tất cả thành phần',
+    filterByType: 'Loại',
+    allTypes: 'Tất cả loại',
+    typePlugin: 'Plugin',
+    typeMCP: 'MCP',
+    typeSkill: 'Kỹ năng',
     requestPlugin: 'Yêu cầu Plugin',
     viewDetails: 'Xem chi tiết',
     deprecated: 'Không còn hỗ trợ',
     deprecatedTooltip: 'Vui lòng cài đặt plugin Công cụ tri thức tương ứng.',
+    filters: {
+      allFormats: 'Tất cả định dạng',
+      more: 'Thêm',
+      advancedTitle: 'Bộ lọc nâng cao',
+      advancedDescription: 'Lọc theo loại phần mở rộng',
+      technicalType: 'Loại kỹ thuật',
+    },
+    allExtensions: 'Tất cả phần mở rộng',
     tags: {
       filterByTags: 'Lọc theo thẻ',
       selected: 'đã chọn',

web/src/i18n/locales/zh-Hans.ts

@@ -35,6 +35,7 @@ const zhHans = {
     delete: '删除',
     add: '添加',
     select: '请选择',
+    skill: '技能',
     cancel: '取消',
     submit: '提交',
     error: '错误',
@@ -590,6 +591,11 @@ const zhHans = {
     markAsReadFailed: '标记为已读失败',
     filterByComponent: '组件',
     allComponents: '全部组件',
+    filterByType: '类型',
+    allTypes: '全部类型',
+    typePlugin: '插件',
+    typeMCP: 'MCP',
+    typeSkill: '技能',
     requestPlugin: '请求插件',
     tags: {
       filterByTags: '按标签筛选',
@@ -598,6 +604,14 @@ const zhHans = {
       clearAll: '清空',
       noTags: '暂无标签',
     },
+    filters: {
+      allFormats: '全部格式',
+      more: '更多',
+      advancedTitle: '高级筛选',
+      advancedDescription: '按扩展类型筛选',
+      technicalType: '技术类型',
+    },
+    allExtensions: '全部扩展',
     viewDetails: '查看详情',
     deprecated: '已弃用',
     deprecatedTooltip: '请安装对应「知识引擎」插件',

web/src/i18n/locales/zh-Hant.ts

@@ -35,6 +35,7 @@ const zhHant = {
     delete: '刪除',
     add: '新增',
     select: '請選擇',
+    skill: '技能',
     cancel: '取消',
     submit: '提交',
     error: '錯誤',
@@ -590,6 +591,11 @@ const zhHant = {
     markAsReadFailed: '標記為已讀失敗',
     filterByComponent: '組件',
     allComponents: '全部組件',
+    filterByType: '類型',
+    allTypes: '全部類型',
+    typePlugin: '插件',
+    typeMCP: 'MCP',
+    typeSkill: '技能',
     requestPlugin: '請求插件',
     tags: {
       filterByTags: '按標籤篩選',
@@ -598,6 +604,14 @@ const zhHant = {
       clearAll: '清空',
       noTags: '暫無標籤',
     },
+    filters: {
+      allFormats: '全部格式',
+      more: '更多',
+      advancedTitle: '高級篩選',
+      advancedDescription: '按擴展類型篩選',
+      technicalType: '技術類型',
+    },
+    allExtensions: '全部擴展',
     viewDetails: '查看詳情',
     deprecated: '已棄用',
     deprecatedTooltip: '請安裝對應「知識引擎」插件',