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Author SHA1 Message Date
Tim 28efd376b6 feat: add MCP search service 2025-10-24 17:06:13 +08:00
13 changed files with 318 additions and 532 deletions
-9
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@@ -7,15 +7,6 @@ REDIS_PORT=6379
RABBITMQ_PORT=5672 RABBITMQ_PORT=5672
RABBITMQ_MANAGEMENT_PORT=15672 RABBITMQ_MANAGEMENT_PORT=15672
# === MCP Server ===
OPENISLE_MCP_TRANSPORT=http
OPENISLE_MCP_HOST=0.0.0.0
OPENISLE_MCP_PORT=8974
OPENISLE_API_BASE_URL=http://springboot:8080
OPENISLE_API_TIMEOUT=10
OPENISLE_MCP_DEFAULT_LIMIT=20
OPENISLE_MCP_SNIPPET_LENGTH=160
# === OpenSearch Configuration === # === OpenSearch Configuration ===
OPENSEARCH_PORT=9200 OPENSEARCH_PORT=9200
OPENSEARCH_METRICS_PORT=9600 OPENSEARCH_METRICS_PORT=9600
+1
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@@ -17,6 +17,7 @@ dist
# misc # misc
.DS_Store .DS_Store
__pycache__/
*.pem *.pem
npm-debug.log* npm-debug.log*
yarn-debug.log* yarn-debug.log*
-1
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@@ -28,7 +28,6 @@ OpenIsle 是一个使用 Spring Boot 和 Vue 3 构建的全栈开源社区平台
- 支持图片上传,默认使用腾讯云 COS 扩展 - 支持图片上传,默认使用腾讯云 COS 扩展
- 默认头像使用 DiceBear Avatars,可通过 `AVATAR_STYLE``AVATAR_SIZE` 环境变量自定义主题和大小 - 默认头像使用 DiceBear Avatars,可通过 `AVATAR_STYLE``AVATAR_SIZE` 环境变量自定义主题和大小
- 浏览器推送通知,离开网站也能及时收到提醒 - 浏览器推送通知,离开网站也能及时收到提醒
- 新增 Python MCP 搜索服务,方便 AI 助手通过统一协议检索社区内容
## 🌟 项目优势 ## 🌟 项目优势
+26 -28
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@@ -178,34 +178,6 @@ services:
- dev - dev
- prod - prod
mcp-server:
build:
context: ../mcp
dockerfile: Dockerfile
container_name: ${COMPOSE_PROJECT_NAME}-openisle-mcp
env_file:
- ${ENV_FILE:-../.env}
environment:
OPENISLE_API_BASE_URL: ${OPENISLE_API_BASE_URL:-http://springboot:8080}
OPENISLE_API_TIMEOUT: ${OPENISLE_API_TIMEOUT:-10}
OPENISLE_MCP_DEFAULT_LIMIT: ${OPENISLE_MCP_DEFAULT_LIMIT:-20}
OPENISLE_MCP_SNIPPET_LENGTH: ${OPENISLE_MCP_SNIPPET_LENGTH:-160}
OPENISLE_MCP_TRANSPORT: ${OPENISLE_MCP_TRANSPORT:-http}
OPENISLE_MCP_HOST: 0.0.0.0
OPENISLE_MCP_PORT: ${OPENISLE_MCP_PORT:-8974}
ports:
- "${OPENISLE_MCP_PORT:-8974}:${OPENISLE_MCP_PORT:-8974}"
depends_on:
springboot:
condition: service_started
restart: unless-stopped
networks:
- openisle-network
profiles:
- dev
- dev_local_backend
- prod
websocket-service: websocket-service:
image: maven:3.9-eclipse-temurin-17 image: maven:3.9-eclipse-temurin-17
container_name: ${COMPOSE_PROJECT_NAME}-openisle-websocket container_name: ${COMPOSE_PROJECT_NAME}-openisle-websocket
@@ -241,6 +213,32 @@ services:
- dev_local_backend - dev_local_backend
- prod - prod
mcp-service:
build:
context: ..
dockerfile: mcp/Dockerfile
container_name: ${COMPOSE_PROJECT_NAME}-openisle-mcp
env_file:
- ${ENV_FILE:-../.env}
environment:
FASTMCP_HOST: 0.0.0.0
FASTMCP_PORT: ${MCP_PORT:-8765}
OPENISLE_BACKEND_URL: ${OPENISLE_BACKEND_URL:-http://springboot:8080}
OPENISLE_BACKEND_TIMEOUT: ${OPENISLE_BACKEND_TIMEOUT:-10}
OPENISLE_MCP_TRANSPORT: ${OPENISLE_MCP_TRANSPORT:-sse}
OPENISLE_MCP_SSE_MOUNT_PATH: ${OPENISLE_MCP_SSE_MOUNT_PATH:-/mcp}
ports:
- "${MCP_PORT:-8765}:${MCP_PORT:-8765}"
depends_on:
springboot:
condition: service_healthy
restart: unless-stopped
networks:
- openisle-network
profiles:
- dev
- prod
frontend_dev: frontend_dev:
image: node:20 image: node:20
container_name: ${COMPOSE_PROJECT_NAME}-openisle-frontend-dev container_name: ${COMPOSE_PROJECT_NAME}-openisle-frontend-dev
+9 -19
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@@ -1,27 +1,17 @@
# syntax=docker/dockerfile:1 FROM python:3.11-slim AS runtime
FROM python:3.11-slim AS base ENV PYTHONUNBUFFERED=1 \
PIP_NO_CACHE_DIR=1
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1
WORKDIR /app WORKDIR /app
RUN apt-get update && apt-get install -y --no-install-recommends \ COPY mcp/pyproject.toml /app/pyproject.toml
build-essential \ COPY mcp/README.md /app/README.md
&& rm -rf /var/lib/apt/lists/* COPY mcp/src /app/src
COPY pyproject.toml README.md ./
COPY src ./src
RUN pip install --upgrade pip \ RUN pip install --upgrade pip \
&& pip install --no-cache-dir . \ && pip install .
&& pip cache purge
ENV OPENISLE_MCP_TRANSPORT=http \ EXPOSE 8765
OPENISLE_MCP_HOST=0.0.0.0 \
OPENISLE_MCP_PORT=8974
EXPOSE 8974 CMD ["openisle-mcp"]
ENTRYPOINT ["openisle-mcp"]
+20 -32
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@@ -1,25 +1,14 @@
# OpenIsle MCP Server # OpenIsle MCP Server
This package provides a Python implementation of a Model Context Protocol (MCP) server for OpenIsle. The server focuses on the community search APIs so that AI assistants and other MCP-aware clients can discover OpenIsle users, posts, categories, comments, and tags. Additional capabilities such as content creation tools can be layered on later without changing the transport or deployment model. This package provides a [Model Context Protocol](https://github.com/modelcontextprotocol) (MCP) server that exposes the OpenIsle
search capabilities to AI assistants. The server wraps the existing Spring Boot backend and currently provides a single `search`
tool. Future iterations can extend the server with additional functionality such as publishing new posts or moderating content.
## Features ## Features
- ✅ Implements the MCP tooling interface using [FastMCP](https://github.com/modelcontextprotocol/fastmcp). - 🔍 **Global search** — delegates to the existing `/api/search/global` endpoint exposed by the OpenIsle backend.
- 🔍 Exposes a `search` tool that proxies requests to the existing OpenIsle REST endpoints and normalises the response payload. - 🧠 **Structured results** — responses include highlights and deep links so AI clients can present the results cleanly.
- ⚙️ Configurable through environment variables for API base URL, timeout, result limits, and snippet size. - ⚙️ **Configurable** — point the server at any reachable OpenIsle backend by setting environment variables.
- 🐳 Packaged with a Docker image so it can be launched alongside the other OpenIsle services.
## Environment variables
| Variable | Default | Description |
| --- | --- | --- |
| `OPENISLE_API_BASE_URL` | `http://springboot:8080` | Base URL of the OpenIsle backend REST API. |
| `OPENISLE_API_TIMEOUT` | `10` | Timeout (in seconds) used when calling the backend search endpoints. |
| `OPENISLE_MCP_DEFAULT_LIMIT` | `20` | Default maximum number of search results to return when the caller does not provide a limit. Use `0` or a negative number to disable limiting. |
| `OPENISLE_MCP_SNIPPET_LENGTH` | `160` | Maximum length (in characters) of the normalised summary snippet returned by the MCP tool. |
| `OPENISLE_MCP_TRANSPORT` | `stdio` | Transport used when running the server directly. Set to `http` when running inside Docker. |
| `OPENISLE_MCP_HOST` | `127.0.0.1` | Bind host used when the transport is HTTP/SSE. |
| `OPENISLE_MCP_PORT` | `8974` | Bind port used when the transport is HTTP/SSE. |
## Local development ## Local development
@@ -27,25 +16,24 @@ This package provides a Python implementation of a Model Context Protocol (MCP)
cd mcp cd mcp
python -m venv .venv python -m venv .venv
source .venv/bin/activate source .venv/bin/activate
pip install --upgrade pip
pip install -e . pip install -e .
OPENISLE_API_BASE_URL=http://localhost:8080 OPENISLE_MCP_TRANSPORT=http openisle-mcp openisle-mcp --transport stdio # or "sse"/"streamable-http"
``` ```
By default the server listens over stdio, which is useful when integrating with MCP-aware IDEs. When the `OPENISLE_MCP_TRANSPORT` variable is set to `http` the server will expose an HTTP transport on `OPENISLE_MCP_HOST:OPENISLE_MCP_PORT`. Environment variables:
## Docker image | Variable | Description | Default |
| --- | --- | --- |
| `OPENISLE_BACKEND_URL` | Base URL of the Spring Boot backend | `http://springboot:8080` |
| `OPENISLE_BACKEND_TIMEOUT` | Timeout (seconds) for backend HTTP calls | `10` |
| `OPENISLE_PUBLIC_BASE_URL` | Optional base URL used to build deep links in search results | *(unset)* |
| `OPENISLE_MCP_TRANSPORT` | MCP transport (`stdio`, `sse`, `streamable-http`) | `stdio` |
| `OPENISLE_MCP_SSE_MOUNT_PATH` | Mount path when using SSE transport | `/mcp` |
| `FASTMCP_HOST` | Host for SSE / HTTP transports | `127.0.0.1` |
| `FASTMCP_PORT` | Port for SSE / HTTP transports | `8000` |
The accompanying `Dockerfile` builds a minimal image that installs the package and starts the MCP server. The root Docker Compose manifest is configured to launch this service and connect it to the same internal network as the Spring Boot API so the MCP tools can reach the search endpoints. ## Docker
## MCP tool contract A dedicated Docker image is provided and wired into `docker-compose.yaml`. The container listens on
`${MCP_PORT:-8765}` and connects to the backend service running in the same compose stack.
The `search` tool accepts the following arguments:
- `keyword` (string, required): Search phrase passed directly to the OpenIsle API.
- `scope` (string, optional): One of `global`, `posts`, `posts_content`, `posts_title`, or `users`. Defaults to `global`.
- `limit` (integer, optional): Overrides the default limit from `OPENISLE_MCP_DEFAULT_LIMIT`.
The tool returns a JSON object containing both the raw API response and a normalised representation with concise titles, subtitles, and snippets for each result.
Future tools (for example posting or moderation helpers) can be added within this package and exposed via additional decorators without changing the deployment setup.
+14 -15
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@@ -1,30 +1,29 @@
[build-system] [build-system]
requires = ["hatchling>=1.25.0"] requires = ["setuptools>=68", "wheel"]
build-backend = "hatchling.build" build-backend = "setuptools.build_meta"
[project] [project]
name = "openisle-mcp" name = "openisle-mcp"
version = "0.1.0" version = "0.1.0"
description = "Model Context Protocol server exposing OpenIsle search functionality." description = "Model Context Protocol server exposing OpenIsle search capabilities"
readme = "README.md" readme = "README.md"
authors = [{name = "OpenIsle Team"}]
license = {text = "MIT"} license = {text = "MIT"}
authors = [{name = "OpenIsle Contributors"}]
requires-python = ">=3.11" requires-python = ">=3.11"
dependencies = [ dependencies = [
"fastmcp>=2.12.5", "mcp>=1.19.0",
"httpx>=0.28.1", "httpx>=0.28.0",
"pydantic>=2.7", "pydantic>=2.12.0",
] ]
[project.scripts] [project.scripts]
openisle-mcp = "openisle_mcp.server:main" openisle-mcp = "openisle_mcp.server:main"
[tool.hatch.build.targets.wheel] [tool.setuptools]
packages = ["src/openisle_mcp"] package-dir = {"" = "src"}
[tool.hatch.build.targets.sdist] [tool.setuptools.packages.find]
include = [ where = ["src"]
"src/openisle_mcp",
"README.md", [tool.setuptools.package-data]
"pyproject.toml", openisle_mcp = ["py.typed"]
]
+7 -2
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@@ -1,5 +1,10 @@
"""OpenIsle MCP server package.""" """OpenIsle MCP server package."""
from .server import main from importlib import metadata
__all__ = ["main"] try:
__version__ = metadata.version("openisle-mcp")
except metadata.PackageNotFoundError: # pragma: no cover - best effort during dev
__version__ = "0.0.0"
__all__ = ["__version__"]
+66 -205
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@@ -1,218 +1,79 @@
"""HTTP client wrappers for interacting with the OpenIsle backend.""" """HTTP client for talking to the OpenIsle backend."""
from __future__ import annotations from __future__ import annotations
import html import json
import re import logging
from typing import Any, Iterable from typing import List
import httpx import httpx
from pydantic import ValidationError
from .models import NormalizedSearchResult, SearchResponse, SearchScope from .models import BackendSearchResult
from .settings import Settings
_TAG_RE = re.compile(r"<[^>]+>") __all__ = ["BackendClientError", "OpenIsleBackendClient"]
_WHITESPACE_RE = re.compile(r"\s+")
logger = logging.getLogger(__name__)
class SearchClient: class BackendClientError(RuntimeError):
"""High level client around the OpenIsle search API.""" """Raised when the backend cannot fulfil a request."""
_ENDPOINTS: dict[SearchScope, str] = {
SearchScope.GLOBAL: "/api/search/global",
SearchScope.POSTS: "/api/search/posts",
SearchScope.POSTS_CONTENT: "/api/search/posts/content",
SearchScope.POSTS_TITLE: "/api/search/posts/title",
SearchScope.USERS: "/api/search/users",
}
def __init__(self, settings: Settings) -> None:
self._base_url = settings.sanitized_base_url()
self._timeout = settings.request_timeout
self._default_limit = settings.default_limit
self._snippet_length = settings.snippet_length
self._client = httpx.AsyncClient(
base_url=self._base_url,
timeout=self._timeout,
headers={"Accept": "application/json"},
)
async def aclose(self) -> None:
await self._client.aclose()
def endpoint_path(self, scope: SearchScope) -> str:
return self._ENDPOINTS[scope]
def endpoint_url(self, scope: SearchScope) -> str:
return f"{self._base_url}{self.endpoint_path(scope)}"
async def search(
self,
keyword: str,
scope: SearchScope,
*,
limit: int | None = None,
) -> SearchResponse:
"""Execute a search request and normalise the results."""
keyword = keyword.strip()
effective_limit = self._resolve_limit(limit)
if not keyword:
return SearchResponse(
keyword=keyword,
scope=scope,
endpoint=self.endpoint_url(scope),
limit=effective_limit,
total_results=0,
returned_results=0,
normalized=[],
raw=[],
)
response = await self._client.get(
self.endpoint_path(scope),
params={"keyword": keyword},
)
response.raise_for_status()
payload = response.json()
if not isinstance(payload, list): # pragma: no cover - defensive programming
raise ValueError("Search API did not return a JSON array")
total_results = len(payload)
items = payload if effective_limit is None else payload[:effective_limit]
normalized = [self._normalise_item(scope, item) for item in items]
return SearchResponse(
keyword=keyword,
scope=scope,
endpoint=self.endpoint_url(scope),
limit=effective_limit,
total_results=total_results,
returned_results=len(items),
normalized=normalized,
raw=items,
)
def _resolve_limit(self, requested: int | None) -> int | None:
value = requested if requested is not None else self._default_limit
if value is None:
return None
if value <= 0:
return None
return value
def _normalise_item(
self,
scope: SearchScope,
item: Any,
) -> NormalizedSearchResult:
"""Normalise raw API objects into a consistent structure."""
if not isinstance(item, dict): # pragma: no cover - defensive programming
return NormalizedSearchResult(type=scope.value, metadata={"raw": item})
if scope == SearchScope.GLOBAL:
return self._normalise_global(item)
if scope in {SearchScope.POSTS, SearchScope.POSTS_CONTENT, SearchScope.POSTS_TITLE}:
return self._normalise_post(item)
if scope == SearchScope.USERS:
return self._normalise_user(item)
return NormalizedSearchResult(type=scope.value, metadata=item)
def _normalise_global(self, item: dict[str, Any]) -> NormalizedSearchResult:
highlights = {
"title": item.get("highlightedText"),
"subtitle": item.get("highlightedSubText"),
"snippet": item.get("highlightedExtra"),
}
snippet_source = highlights.get("snippet") or item.get("extra")
metadata = {
"postId": item.get("postId"),
"highlights": {k: v for k, v in highlights.items() if v},
}
return NormalizedSearchResult(
type=str(item.get("type", "result")),
id=_safe_int(item.get("id")),
title=highlights.get("title") or _safe_str(item.get("text")),
subtitle=highlights.get("subtitle") or _safe_str(item.get("subText")),
snippet=self._snippet(snippet_source),
metadata={k: v for k, v in metadata.items() if v not in (None, {}, [])},
)
def _normalise_post(self, item: dict[str, Any]) -> NormalizedSearchResult:
author = _safe_dict(item.get("author"))
category = _safe_dict(item.get("category"))
tags = [tag.get("name") for tag in _safe_iter(item.get("tags")) if isinstance(tag, dict)]
metadata = {
"author": author.get("username"),
"category": category.get("name"),
"tags": tags,
"views": item.get("views"),
"commentCount": item.get("commentCount"),
"status": item.get("status"),
"apiUrl": f"{self._base_url}/api/posts/{item.get('id')}" if item.get("id") else None,
}
return NormalizedSearchResult(
type="post",
id=_safe_int(item.get("id")),
title=_safe_str(item.get("title")),
subtitle=_safe_str(category.get("name")),
snippet=self._snippet(item.get("content")),
metadata={k: v for k, v in metadata.items() if v not in (None, [], {})},
)
def _normalise_user(self, item: dict[str, Any]) -> NormalizedSearchResult:
metadata = {
"followers": item.get("followers"),
"following": item.get("following"),
"totalViews": item.get("totalViews"),
"role": item.get("role"),
"subscribed": item.get("subscribed"),
"apiUrl": f"{self._base_url}/api/users/{item.get('id')}" if item.get("id") else None,
}
return NormalizedSearchResult(
type="user",
id=_safe_int(item.get("id")),
title=_safe_str(item.get("username")),
subtitle=_safe_str(item.get("email") or item.get("role")),
snippet=self._snippet(item.get("introduction")),
metadata={k: v for k, v in metadata.items() if v not in (None, [], {})},
)
def _snippet(self, value: Any) -> str | None:
text = _safe_str(value)
if not text:
return None
text = html.unescape(text)
text = _TAG_RE.sub(" ", text)
text = _WHITESPACE_RE.sub(" ", text).strip()
if not text:
return None
if len(text) <= self._snippet_length:
return text
return text[: self._snippet_length - 1].rstrip() + ""
def _safe_int(value: Any) -> int | None: class OpenIsleBackendClient:
try: """Tiny wrapper around the Spring Boot search endpoints."""
return int(value)
except (TypeError, ValueError): # pragma: no cover - defensive def __init__(self, base_url: str, timeout: float = 10.0) -> None:
return None if not base_url:
raise ValueError("base_url must not be empty")
self._base_url = base_url.rstrip("/")
timeout = timeout if timeout > 0 else 10.0
self._timeout = httpx.Timeout(timeout, connect=timeout, read=timeout)
@property
def base_url(self) -> str:
return self._base_url
async def search_global(self, keyword: str) -> List[BackendSearchResult]:
"""Call `/api/search/global` and normalise the payload."""
url = f"{self._base_url}/api/search/global"
params = {"keyword": keyword}
headers = {"Accept": "application/json"}
logger.debug("Calling OpenIsle backend", extra={"url": url, "params": params})
try:
async with httpx.AsyncClient(timeout=self._timeout, headers=headers, follow_redirects=True) as client:
response = await client.get(url, params=params)
response.raise_for_status()
except httpx.HTTPStatusError as exc: # pragma: no cover - network errors are rare in tests
body_preview = _truncate_body(exc.response.text)
raise BackendClientError(
f"Backend returned HTTP {exc.response.status_code}: {body_preview}"
) from exc
except httpx.RequestError as exc: # pragma: no cover - network errors are rare in tests
raise BackendClientError(f"Failed to reach backend: {exc}") from exc
try:
payload = response.json()
except json.JSONDecodeError as exc:
raise BackendClientError("Backend returned invalid JSON") from exc
if not isinstance(payload, list):
raise BackendClientError("Unexpected search payload type; expected a list")
results: list[BackendSearchResult] = []
for item in payload:
try:
results.append(BackendSearchResult.model_validate(item))
except ValidationError as exc:
raise BackendClientError(f"Invalid search result payload: {exc}") from exc
return results
def _safe_str(value: Any) -> str | None: def _truncate_body(body: str, limit: int = 200) -> str:
if value is None: body = body.strip()
return None if len(body) <= limit:
text = str(value).strip() return body
return text or None return f"{body[:limit]}"
def _safe_dict(value: Any) -> dict[str, Any]:
return value if isinstance(value, dict) else {}
def _safe_iter(value: Any) -> Iterable[Any]:
if isinstance(value, list | tuple | set):
return value
return []
+39 -52
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@@ -1,71 +1,58 @@
"""Shared models for the OpenIsle MCP server.""" """Pydantic models used by the OpenIsle MCP server."""
from __future__ import annotations from __future__ import annotations
from enum import Enum from typing import Dict, Optional
from typing import Any
from pydantic import BaseModel, Field from pydantic import BaseModel, ConfigDict, Field
__all__ = [
"BackendSearchResult",
"SearchResult",
"SearchResponse",
]
class SearchScope(str, Enum): class BackendSearchResult(BaseModel):
"""Supported search endpoints.""" """Shape of the payload returned by the OpenIsle backend."""
GLOBAL = "global" type: str
POSTS = "posts" id: Optional[int] = None
POSTS_CONTENT = "posts_content" text: Optional[str] = None
POSTS_TITLE = "posts_title" sub_text: Optional[str] = Field(default=None, alias="subText")
USERS = "users" extra: Optional[str] = None
post_id: Optional[int] = Field(default=None, alias="postId")
highlighted_text: Optional[str] = Field(default=None, alias="highlightedText")
highlighted_sub_text: Optional[str] = Field(default=None, alias="highlightedSubText")
highlighted_extra: Optional[str] = Field(default=None, alias="highlightedExtra")
def __str__(self) -> str: # pragma: no cover - convenience for logging model_config = ConfigDict(populate_by_name=True, extra="ignore")
return self.value
class NormalizedSearchResult(BaseModel): class SearchResult(BaseModel):
"""Compact structure returned by the MCP search tool.""" """Structured search result returned to MCP clients."""
type: str = Field(description="Entity type, e.g. user, post, comment.") type: str = Field(description="Entity type, e.g. post, comment, user")
id: int | None = Field(default=None, description="Primary identifier of the entity.") id: Optional[int] = Field(default=None, description="Primary identifier for the entity")
title: str | None = Field(default=None, description="Display title for the result.") title: Optional[str] = Field(default=None, description="Primary text to display")
subtitle: str | None = Field(default=None, description="Secondary line of context.") subtitle: Optional[str] = Field(default=None, description="Secondary text (e.g. author or category)")
snippet: str | None = Field(default=None, description="Short summary of the result.") extra: Optional[str] = Field(default=None, description="Additional descriptive snippet")
metadata: dict[str, Any] = Field( post_id: Optional[int] = Field(default=None, description="Associated post id for comment results")
url: Optional[str] = Field(default=None, description="Deep link to the resource inside OpenIsle")
highlights: Dict[str, Optional[str]] = Field(
default_factory=dict, default_factory=dict,
description="Additional attributes extracted from the API response.", description="Highlighted HTML fragments keyed by field name",
) )
model_config = { model_config = ConfigDict(populate_by_name=True)
"extra": "ignore",
}
class SearchResponse(BaseModel): class SearchResponse(BaseModel):
"""Payload returned to MCP clients.""" """Response envelope returned from the MCP search tool."""
keyword: str keyword: str = Field(description="Sanitised keyword that was searched for")
scope: SearchScope total_results: int = Field(description="Total number of results returned by the backend")
endpoint: str limit: int = Field(description="Maximum number of results included in the response")
limit: int | None = Field( results: list[SearchResult] = Field(default_factory=list, description="Search results up to the requested limit")
default=None,
description="Result limit applied to the request. None means unlimited.",
)
total_results: int = Field(
default=0,
description="Total number of items returned by the OpenIsle API before limiting.",
)
returned_results: int = Field(
default=0,
description="Number of items returned to the MCP client after limiting.",
)
normalized: list[NormalizedSearchResult] = Field(
default_factory=list,
description="Normalised representation of each search hit.",
)
raw: list[Any] = Field(
default_factory=list,
description="Raw response objects from the OpenIsle REST API.",
)
model_config = { model_config = ConfigDict(populate_by_name=True)
"extra": "ignore",
}
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+136 -67
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@@ -1,95 +1,164 @@
"""Entrypoint for the OpenIsle MCP server.""" """Entry point for the OpenIsle MCP server."""
from __future__ import annotations from __future__ import annotations
import argparse
import logging
import os import os
from contextlib import asynccontextmanager from typing import Annotated, Optional
from typing import Any
import httpx from mcp.server.fastmcp import Context, FastMCP
from fastmcp import Context, FastMCP from mcp.server.fastmcp import exceptions as mcp_exceptions
from pydantic import Field
from .client import SearchClient from .client import BackendClientError, OpenIsleBackendClient
from .models import SearchResponse, SearchScope from .models import BackendSearchResult, SearchResponse, SearchResult
from .settings import Settings
__all__ = ["main"] logger = logging.getLogger(__name__)
APP_NAME = "openisle-mcp"
DEFAULT_BACKEND_URL = "http://springboot:8080"
DEFAULT_TRANSPORT = "stdio"
DEFAULT_TIMEOUT = 10.0
DEFAULT_LIMIT = 20
MAX_LIMIT = 50
def _create_lifespan(settings: Settings): server = FastMCP(
@asynccontextmanager APP_NAME,
async def lifespan(app: FastMCP):
client = SearchClient(settings)
setattr(app, "_search_client", client)
try:
yield {"client": client}
finally:
await client.aclose()
if hasattr(app, "_search_client"):
delattr(app, "_search_client")
return lifespan
_settings = Settings.from_env()
mcp = FastMCP(
name="OpenIsle Search",
version="0.1.0",
instructions=( instructions=(
"Provides access to OpenIsle search endpoints for retrieving users, posts, " "Use the `search` tool to query OpenIsle content. "
"comments, tags, and categories." "Results include posts, comments, users, categories, and tags."
), ),
lifespan=_create_lifespan(_settings),
) )
@mcp.tool("search") def _env(name: str, default: Optional[str] = None) -> Optional[str]:
async def search( value = os.getenv(name, default)
keyword: str, if value is None:
scope: SearchScope = SearchScope.GLOBAL, return None
limit: int | None = None, trimmed = value.strip()
ctx: Context | None = None, return trimmed or default
) -> dict[str, Any]:
"""Perform a search against the OpenIsle backend."""
client = _resolve_client(ctx)
def _load_timeout() -> float:
raw = _env("OPENISLE_BACKEND_TIMEOUT", str(DEFAULT_TIMEOUT))
try: try:
response: SearchResponse = await client.search(keyword=keyword, scope=scope, limit=limit) timeout = float(raw) if raw is not None else DEFAULT_TIMEOUT
except httpx.HTTPError as exc: except ValueError:
message = f"OpenIsle search request failed: {exc}".rstrip() logger.warning("Invalid OPENISLE_BACKEND_TIMEOUT value '%s', falling back to %s", raw, DEFAULT_TIMEOUT)
raise RuntimeError(message) from exc return DEFAULT_TIMEOUT
if timeout <= 0:
logger.warning("Non-positive OPENISLE_BACKEND_TIMEOUT %s, falling back to %s", timeout, DEFAULT_TIMEOUT)
return DEFAULT_TIMEOUT
return timeout
payload = response.model_dump()
payload["transport"] = { _BACKEND_CLIENT = OpenIsleBackendClient(
"scope": scope.value, base_url=_env("OPENISLE_BACKEND_URL", DEFAULT_BACKEND_URL) or DEFAULT_BACKEND_URL,
"endpoint": client.endpoint_url(scope), timeout=_load_timeout(),
)
_PUBLIC_BASE_URL = _env("OPENISLE_PUBLIC_BASE_URL")
def _build_url(result: BackendSearchResult) -> Optional[str]:
if not _PUBLIC_BASE_URL:
return None
base = _PUBLIC_BASE_URL.rstrip("/")
if result.type in {"post", "post_title"} and result.id is not None:
return f"{base}/posts/{result.id}"
if result.type == "comment" and result.post_id is not None:
anchor = f"#comment-{result.id}" if result.id is not None else ""
return f"{base}/posts/{result.post_id}{anchor}"
if result.type == "user" and result.id is not None:
return f"{base}/users/{result.id}"
if result.type == "category" and result.id is not None:
return f"{base}/?categoryId={result.id}"
if result.type == "tag" and result.id is not None:
return f"{base}/?tagIds={result.id}"
return None
def _to_search_result(result: BackendSearchResult) -> SearchResult:
highlights = {
"text": result.highlighted_text,
"subText": result.highlighted_sub_text,
"extra": result.highlighted_extra,
} }
return payload # Remove empty highlight entries to keep the payload clean
highlights = {key: value for key, value in highlights.items() if value}
return SearchResult(
type=result.type,
id=result.id,
title=result.text,
subtitle=result.sub_text,
extra=result.extra,
post_id=result.post_id,
url=_build_url(result),
highlights=highlights,
)
def _resolve_client(ctx: Context | None) -> SearchClient: KeywordParam = Annotated[str, Field(description="Keyword to search for", min_length=1)]
app = ctx.fastmcp if ctx is not None else mcp LimitParam = Annotated[
client = getattr(app, "_search_client", None) int,
if client is None: Field(ge=1, le=MAX_LIMIT, description=f"Maximum number of results to return (<= {MAX_LIMIT})"),
raise RuntimeError("Search client is not initialised; lifespan hook not executed") ]
return client
@server.tool(name="search", description="Search OpenIsle content")
async def search(keyword: KeywordParam, limit: LimitParam = DEFAULT_LIMIT, ctx: Optional[Context] = None) -> SearchResponse:
"""Run a search query against the OpenIsle backend."""
trimmed = keyword.strip()
if not trimmed:
raise mcp_exceptions.ToolError("Keyword must not be empty")
if ctx is not None:
await ctx.debug(f"Searching OpenIsle for '{trimmed}' (limit={limit})")
try:
raw_results = await _BACKEND_CLIENT.search_global(trimmed)
except BackendClientError as exc:
if ctx is not None:
await ctx.error(f"Search request failed: {exc}")
raise mcp_exceptions.ToolError(f"Search failed: {exc}") from exc
results = [_to_search_result(result) for result in raw_results]
limited = results[:limit]
if ctx is not None:
await ctx.info(
"Search completed",
keyword=trimmed,
total_results=len(results),
returned=len(limited),
)
return SearchResponse(keyword=trimmed, total_results=len(results), limit=limit, results=limited)
def main() -> None: def main() -> None:
"""CLI entrypoint.""" parser = argparse.ArgumentParser(description="Run the OpenIsle MCP server")
parser.add_argument(
"--transport",
choices=["stdio", "sse", "streamable-http"],
default=_env("OPENISLE_MCP_TRANSPORT", DEFAULT_TRANSPORT),
help="Transport protocol to use",
)
parser.add_argument(
"--mount-path",
default=_env("OPENISLE_MCP_SSE_MOUNT_PATH", "/mcp"),
help="Mount path when using the SSE transport",
)
args = parser.parse_args()
transport = os.getenv("OPENISLE_MCP_TRANSPORT", "stdio").strip().lower() logging.basicConfig(level=os.getenv("OPENISLE_MCP_LOG_LEVEL", "INFO"))
show_banner = os.getenv("OPENISLE_MCP_SHOW_BANNER", "true").lower() in {"1", "true", "yes"} logger.info(
run_kwargs: dict[str, Any] = {"show_banner": show_banner} "Starting OpenIsle MCP server", extra={"transport": args.transport, "backend": _BACKEND_CLIENT.base_url}
)
if transport in {"http", "sse", "streamable-http"}: server.run(transport=args.transport, mount_path=args.mount_path)
host = os.getenv("OPENISLE_MCP_HOST", "127.0.0.1")
port = int(os.getenv("OPENISLE_MCP_PORT", "8974"))
run_kwargs.update({"host": host, "port": port})
mcp.run(transport=transport, **run_kwargs)
if __name__ == "__main__": # pragma: no cover - manual execution guard if __name__ == "__main__":
main() main()
-102
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@@ -1,102 +0,0 @@
"""Environment configuration for the MCP server."""
from __future__ import annotations
import os
from typing import Any
from pydantic import BaseModel, Field, ValidationError, field_validator
class Settings(BaseModel):
"""Runtime configuration sourced from environment variables."""
api_base_url: str = Field(
default="http://springboot:8080",
description="Base URL of the OpenIsle backend REST API.",
)
request_timeout: float = Field(
default=10.0,
description="Timeout in seconds for outgoing HTTP requests.",
ge=0.1,
)
default_limit: int = Field(
default=20,
description="Default maximum number of results returned by the search tool.",
)
snippet_length: int = Field(
default=160,
description="Maximum length for the normalised snippet field.",
ge=40,
)
model_config = {
"extra": "ignore",
"validate_assignment": True,
}
@field_validator("api_base_url", mode="before")
@classmethod
def _strip_trailing_slash(cls, value: Any) -> Any:
if isinstance(value, str):
value = value.strip()
if value.endswith("/"):
return value.rstrip("/")
return value
@field_validator("default_limit", mode="before")
@classmethod
def _parse_default_limit(cls, value: Any) -> Any:
if isinstance(value, str) and value.strip():
try:
return int(value)
except ValueError as exc: # pragma: no cover - defensive
raise ValueError("default_limit must be an integer") from exc
return value
@field_validator("snippet_length", mode="before")
@classmethod
def _parse_snippet_length(cls, value: Any) -> Any:
if isinstance(value, str) and value.strip():
try:
return int(value)
except ValueError as exc: # pragma: no cover - defensive
raise ValueError("snippet_length must be an integer") from exc
return value
@field_validator("request_timeout", mode="before")
@classmethod
def _parse_timeout(cls, value: Any) -> Any:
if isinstance(value, str) and value.strip():
try:
return float(value)
except ValueError as exc: # pragma: no cover - defensive
raise ValueError("request_timeout must be a number") from exc
return value
@classmethod
def from_env(cls) -> "Settings":
"""Build a settings object using environment variables."""
data: dict[str, Any] = {}
mapping = {
"api_base_url": "OPENISLE_API_BASE_URL",
"request_timeout": "OPENISLE_API_TIMEOUT",
"default_limit": "OPENISLE_MCP_DEFAULT_LIMIT",
"snippet_length": "OPENISLE_MCP_SNIPPET_LENGTH",
}
for field, env_key in mapping.items():
value = os.getenv(env_key)
if value is not None and value != "":
data[field] = value
try:
return cls.model_validate(data)
except ValidationError as exc: # pragma: no cover - validation errors surface early
raise ValueError(
"Invalid MCP settings derived from environment variables"
) from exc
def sanitized_base_url(self) -> str:
"""Return the API base URL without trailing slashes."""
return self.api_base_url.rstrip("/")