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Author SHA1 Message Date
Tim bcd6a3249d feat: add MCP search server 2025-10-25 21:58:11 +08:00
13 changed files with 532 additions and 318 deletions
+9
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@@ -7,6 +7,15 @@ 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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@@ -17,7 +17,6 @@ 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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@@ -28,6 +28,7 @@ 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
+28 -26
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@@ -178,6 +178,34 @@ 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
@@ -213,32 +241,6 @@ 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
+19 -9
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@@ -1,17 +1,27 @@
FROM python:3.11-slim AS runtime # syntax=docker/dockerfile:1
ENV PYTHONUNBUFFERED=1 \ FROM python:3.11-slim AS base
PIP_NO_CACHE_DIR=1
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1
WORKDIR /app WORKDIR /app
COPY mcp/pyproject.toml /app/pyproject.toml RUN apt-get update && apt-get install -y --no-install-recommends \
COPY mcp/README.md /app/README.md build-essential \
COPY mcp/src /app/src && rm -rf /var/lib/apt/lists/*
COPY pyproject.toml README.md ./
COPY src ./src
RUN pip install --upgrade pip \ RUN pip install --upgrade pip \
&& pip install . && pip install --no-cache-dir . \
&& pip cache purge
EXPOSE 8765 ENV OPENISLE_MCP_TRANSPORT=http \
OPENISLE_MCP_HOST=0.0.0.0 \
OPENISLE_MCP_PORT=8974
CMD ["openisle-mcp"] EXPOSE 8974
ENTRYPOINT ["openisle-mcp"]
+32 -20
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@@ -1,14 +1,25 @@
# OpenIsle MCP Server # OpenIsle MCP Server
This package provides a [Model Context Protocol](https://github.com/modelcontextprotocol) (MCP) server that exposes the OpenIsle 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.
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
- 🔍 **Global search** — delegates to the existing `/api/search/global` endpoint exposed by the OpenIsle backend. - ✅ Implements the MCP tooling interface using [FastMCP](https://github.com/modelcontextprotocol/fastmcp).
- 🧠 **Structured results** — responses include highlights and deep links so AI clients can present the results cleanly. - 🔍 Exposes a `search` tool that proxies requests to the existing OpenIsle REST endpoints and normalises the response payload.
- ⚙️ **Configurable** — point the server at any reachable OpenIsle backend by setting environment variables. - ⚙️ Configurable through environment variables for API base URL, timeout, result limits, and snippet size.
- 🐳 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
@@ -16,24 +27,25 @@ tool. Future iterations can extend the server with additional functionality such
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-mcp --transport stdio # or "sse"/"streamable-http" OPENISLE_API_BASE_URL=http://localhost:8080 OPENISLE_MCP_TRANSPORT=http openisle-mcp
``` ```
Environment variables: 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`.
| Variable | Description | Default | ## Docker image
| --- | --- | --- |
| `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` |
## Docker 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.
A dedicated Docker image is provided and wired into `docker-compose.yaml`. The container listens on ## MCP tool contract
`${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.
+15 -14
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@@ -1,29 +1,30 @@
[build-system] [build-system]
requires = ["setuptools>=68", "wheel"] requires = ["hatchling>=1.25.0"]
build-backend = "setuptools.build_meta" build-backend = "hatchling.build"
[project] [project]
name = "openisle-mcp" name = "openisle-mcp"
version = "0.1.0" version = "0.1.0"
description = "Model Context Protocol server exposing OpenIsle search capabilities" description = "Model Context Protocol server exposing OpenIsle search functionality."
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 = [
"mcp>=1.19.0", "fastmcp>=2.12.5",
"httpx>=0.28.0", "httpx>=0.28.1",
"pydantic>=2.12.0", "pydantic>=2.7",
] ]
[project.scripts] [project.scripts]
openisle-mcp = "openisle_mcp.server:main" openisle-mcp = "openisle_mcp.server:main"
[tool.setuptools] [tool.hatch.build.targets.wheel]
package-dir = {"" = "src"} packages = ["src/openisle_mcp"]
[tool.setuptools.packages.find] [tool.hatch.build.targets.sdist]
where = ["src"] include = [
"src/openisle_mcp",
[tool.setuptools.package-data] "README.md",
openisle_mcp = ["py.typed"] "pyproject.toml",
]
+2 -7
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@@ -1,10 +1,5 @@
"""OpenIsle MCP server package.""" """OpenIsle MCP server package."""
from importlib import metadata from .server import main
try: __all__ = ["main"]
__version__ = metadata.version("openisle-mcp")
except metadata.PackageNotFoundError: # pragma: no cover - best effort during dev
__version__ = "0.0.0"
__all__ = ["__version__"]
+205 -66
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@@ -1,79 +1,218 @@
"""HTTP client for talking to the OpenIsle backend.""" """HTTP client wrappers for interacting with the OpenIsle backend."""
from __future__ import annotations from __future__ import annotations
import json import html
import logging import re
from typing import List from typing import Any, Iterable
import httpx import httpx
from pydantic import ValidationError
from .models import BackendSearchResult from .models import NormalizedSearchResult, SearchResponse, SearchScope
from .settings import Settings
__all__ = ["BackendClientError", "OpenIsleBackendClient"] _TAG_RE = re.compile(r"<[^>]+>")
_WHITESPACE_RE = re.compile(r"\s+")
logger = logging.getLogger(__name__)
class BackendClientError(RuntimeError): class SearchClient:
"""Raised when the backend cannot fulfil a request.""" """High level client around the OpenIsle search API."""
_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() + ""
class OpenIsleBackendClient: def _safe_int(value: Any) -> int | None:
"""Tiny wrapper around the Spring Boot search endpoints.""" try:
return int(value)
def __init__(self, base_url: str, timeout: float = 10.0) -> None: except (TypeError, ValueError): # pragma: no cover - defensive
if not base_url: return None
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 _truncate_body(body: str, limit: int = 200) -> str: def _safe_str(value: Any) -> str | None:
body = body.strip() if value is None:
if len(body) <= limit: return None
return body text = str(value).strip()
return f"{body[:limit]}" return text or None
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 []
+52 -39
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@@ -1,58 +1,71 @@
"""Pydantic models used by the OpenIsle MCP server.""" """Shared models for the OpenIsle MCP server."""
from __future__ import annotations from __future__ import annotations
from typing import Dict, Optional from enum import Enum
from typing import Any
from pydantic import BaseModel, ConfigDict, Field from pydantic import BaseModel, Field
__all__ = [
"BackendSearchResult",
"SearchResult",
"SearchResponse",
]
class BackendSearchResult(BaseModel): class SearchScope(str, Enum):
"""Shape of the payload returned by the OpenIsle backend.""" """Supported search endpoints."""
type: str GLOBAL = "global"
id: Optional[int] = None POSTS = "posts"
text: Optional[str] = None POSTS_CONTENT = "posts_content"
sub_text: Optional[str] = Field(default=None, alias="subText") POSTS_TITLE = "posts_title"
extra: Optional[str] = None USERS = "users"
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")
model_config = ConfigDict(populate_by_name=True, extra="ignore") def __str__(self) -> str: # pragma: no cover - convenience for logging
return self.value
class SearchResult(BaseModel): class NormalizedSearchResult(BaseModel):
"""Structured search result returned to MCP clients.""" """Compact structure returned by the MCP search tool."""
type: str = Field(description="Entity type, e.g. post, comment, user") type: str = Field(description="Entity type, e.g. user, post, comment.")
id: Optional[int] = Field(default=None, description="Primary identifier for the entity") id: int | None = Field(default=None, description="Primary identifier of the entity.")
title: Optional[str] = Field(default=None, description="Primary text to display") title: str | None = Field(default=None, description="Display title for the result.")
subtitle: Optional[str] = Field(default=None, description="Secondary text (e.g. author or category)") subtitle: str | None = Field(default=None, description="Secondary line of context.")
extra: Optional[str] = Field(default=None, description="Additional descriptive snippet") snippet: str | None = Field(default=None, description="Short summary of the result.")
post_id: Optional[int] = Field(default=None, description="Associated post id for comment results") metadata: dict[str, Any] = Field(
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="Highlighted HTML fragments keyed by field name", description="Additional attributes extracted from the API response.",
) )
model_config = ConfigDict(populate_by_name=True) model_config = {
"extra": "ignore",
}
class SearchResponse(BaseModel): class SearchResponse(BaseModel):
"""Response envelope returned from the MCP search tool.""" """Payload returned to MCP clients."""
keyword: str = Field(description="Sanitised keyword that was searched for") keyword: str
total_results: int = Field(description="Total number of results returned by the backend") scope: SearchScope
limit: int = Field(description="Maximum number of results included in the response") endpoint: str
results: list[SearchResult] = Field(default_factory=list, description="Search results up to the requested limit") limit: int | None = Field(
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 = ConfigDict(populate_by_name=True) model_config = {
"extra": "ignore",
}
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+67 -136
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@@ -1,164 +1,95 @@
"""Entry point for the OpenIsle MCP server.""" """Entrypoint for the OpenIsle MCP server."""
from __future__ import annotations from __future__ import annotations
import argparse
import logging
import os import os
from typing import Annotated, Optional from contextlib import asynccontextmanager
from typing import Any
from mcp.server.fastmcp import Context, FastMCP import httpx
from mcp.server.fastmcp import exceptions as mcp_exceptions from fastmcp import Context, FastMCP
from pydantic import Field
from .client import BackendClientError, OpenIsleBackendClient from .client import SearchClient
from .models import BackendSearchResult, SearchResponse, SearchResult from .models import SearchResponse, SearchScope
from .settings import Settings
logger = logging.getLogger(__name__) __all__ = ["main"]
APP_NAME = "openisle-mcp"
DEFAULT_BACKEND_URL = "http://springboot:8080"
DEFAULT_TRANSPORT = "stdio"
DEFAULT_TIMEOUT = 10.0
DEFAULT_LIMIT = 20
MAX_LIMIT = 50
server = FastMCP( def _create_lifespan(settings: Settings):
APP_NAME, @asynccontextmanager
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=(
"Use the `search` tool to query OpenIsle content. " "Provides access to OpenIsle search endpoints for retrieving users, posts, "
"Results include posts, comments, users, categories, and tags." "comments, tags, and categories."
), ),
lifespan=_create_lifespan(_settings),
) )
def _env(name: str, default: Optional[str] = None) -> Optional[str]: @mcp.tool("search")
value = os.getenv(name, default) async def search(
if value is None: keyword: str,
return None scope: SearchScope = SearchScope.GLOBAL,
trimmed = value.strip() limit: int | None = None,
return trimmed or default ctx: Context | None = None,
) -> 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:
timeout = float(raw) if raw is not None else DEFAULT_TIMEOUT response: SearchResponse = await client.search(keyword=keyword, scope=scope, limit=limit)
except ValueError: except httpx.HTTPError as exc:
logger.warning("Invalid OPENISLE_BACKEND_TIMEOUT value '%s', falling back to %s", raw, DEFAULT_TIMEOUT) message = f"OpenIsle search request failed: {exc}".rstrip()
return DEFAULT_TIMEOUT raise RuntimeError(message) from exc
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()
_BACKEND_CLIENT = OpenIsleBackendClient( payload["transport"] = {
base_url=_env("OPENISLE_BACKEND_URL", DEFAULT_BACKEND_URL) or DEFAULT_BACKEND_URL, "scope": scope.value,
timeout=_load_timeout(), "endpoint": client.endpoint_url(scope),
)
_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,
} }
# Remove empty highlight entries to keep the payload clean return payload
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,
)
KeywordParam = Annotated[str, Field(description="Keyword to search for", min_length=1)] def _resolve_client(ctx: Context | None) -> SearchClient:
LimitParam = Annotated[ app = ctx.fastmcp if ctx is not None else mcp
int, client = getattr(app, "_search_client", None)
Field(ge=1, le=MAX_LIMIT, description=f"Maximum number of results to return (<= {MAX_LIMIT})"), if client is None:
] 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:
parser = argparse.ArgumentParser(description="Run the OpenIsle MCP server") """CLI entrypoint."""
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()
logging.basicConfig(level=os.getenv("OPENISLE_MCP_LOG_LEVEL", "INFO")) transport = os.getenv("OPENISLE_MCP_TRANSPORT", "stdio").strip().lower()
logger.info( show_banner = os.getenv("OPENISLE_MCP_SHOW_BANNER", "true").lower() in {"1", "true", "yes"}
"Starting OpenIsle MCP server", extra={"transport": args.transport, "backend": _BACKEND_CLIENT.base_url} run_kwargs: dict[str, Any] = {"show_banner": show_banner}
)
server.run(transport=args.transport, mount_path=args.mount_path) if transport in {"http", "sse", "streamable-http"}:
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__": if __name__ == "__main__": # pragma: no cover - manual execution guard
main() main()
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"""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("/")