feat: add MCP search server

.env.example

@@ -7,6 +7,15 @@ REDIS_PORT=6379
 RABBITMQ_PORT=5672
 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_PORT=9200
 OPENSEARCH_METRICS_PORT=9600

README.md

@@ -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
 - 默认头像使用 DiceBear Avatars，可通过 `AVATAR_STYLE` 和 `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
+- 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
 

deploy/deploy.sh

@@ -40,12 +40,12 @@ echo "👉 Build images ..."
 docker compose -f "$compose_file" --env-file "$env_file" \
   build --pull \
   --build-arg NUXT_ENV=production \
-  frontend_service mcp
+  frontend_service
 
 echo "👉 Recreate & start all target services (no dev profile)..."
 docker compose -f "$compose_file" --env-file "$env_file" \
   up -d --force-recreate --remove-orphans --no-deps \
-  mysql redis rabbitmq websocket-service springboot frontend_service mcp
+  mysql redis rabbitmq websocket-service springboot frontend_service
 
 echo "👉 Current status:"
 docker compose -f "$compose_file" --env-file "$env_file" ps

deploy/deploy_staging.sh

@@ -39,12 +39,12 @@ echo "👉 Build images (staging)..."
 docker compose -f "$compose_file" --env-file "$env_file" \
   build --pull \
   --build-arg NUXT_ENV=staging \
-  frontend_service mcp
+  frontend_service
 
 echo "👉 Recreate & start all target services (no dev profile)..."
 docker compose -f "$compose_file" --env-file "$env_file" \
   up -d --force-recreate --remove-orphans --no-deps \
-  mysql redis rabbitmq websocket-service springboot frontend_service mcp
+  mysql redis rabbitmq websocket-service springboot frontend_service
 
 echo "👉 Current status:"
 docker compose -f "$compose_file" --env-file "$env_file" ps

docker/docker-compose.yaml

@@ -178,24 +178,27 @@ services:
       - dev
       - prod
 
-  mcp:
+  mcp-server:
     build:
-      context: ..
-      dockerfile: docker/mcp.Dockerfile
+      context: ../mcp
+      dockerfile: Dockerfile
     container_name: ${COMPOSE_PROJECT_NAME}-openisle-mcp
     env_file:
       - ${ENV_FILE:-../.env}
     environment:
-      OPENISLE_MCP_BACKEND_BASE_URL: ${OPENISLE_MCP_BACKEND_BASE_URL:-http://springboot:8080}
+      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:-8085}
-      OPENISLE_MCP_TRANSPORT: ${OPENISLE_MCP_TRANSPORT:-streamable-http}
-      OPENISLE_MCP_REQUEST_TIMEOUT: ${OPENISLE_MCP_REQUEST_TIMEOUT:-10.0}
+      OPENISLE_MCP_PORT: ${OPENISLE_MCP_PORT:-8974}
     ports:
-      - "${OPENISLE_MCP_PORT:-8085}:${OPENISLE_MCP_PORT:-8085}"
+      - "${OPENISLE_MCP_PORT:-8974}:${OPENISLE_MCP_PORT:-8974}"
     depends_on:
       springboot:
         condition: service_started
+    restart: unless-stopped
     networks:
       - openisle-network
     profiles:
@@ -203,7 +206,6 @@ services:
       - dev_local_backend
       - prod
 
-
   websocket-service:
     image: maven:3.9-eclipse-temurin-17
     container_name: ${COMPOSE_PROJECT_NAME}-openisle-websocket

docker/mcp.Dockerfile

@@ -1,21 +0,0 @@
-FROM python:3.11-slim AS base
-
-ENV PYTHONDONTWRITEBYTECODE=1 \
-    PYTHONUNBUFFERED=1
-
-WORKDIR /app
-
-COPY mcp/pyproject.toml mcp/README.md ./
-COPY mcp/src ./src
-
-RUN pip install --no-cache-dir --upgrade pip \
-    && pip install --no-cache-dir .
-
-ENV OPENISLE_MCP_HOST=0.0.0.0 \
-    OPENISLE_MCP_PORT=8085 \
-    OPENISLE_MCP_TRANSPORT=streamable-http
-
-EXPOSE 8085
-
-CMD ["openisle-mcp"]
-

mcp/Dockerfile

@@ -0,0 +1,27 @@
+# syntax=docker/dockerfile:1
+
+FROM python:3.11-slim AS base
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY pyproject.toml README.md ./
+COPY src ./src
+
+RUN pip install --upgrade pip \
+    && pip install --no-cache-dir . \
+    && pip cache purge
+
+ENV OPENISLE_MCP_TRANSPORT=http \
+    OPENISLE_MCP_HOST=0.0.0.0 \
+    OPENISLE_MCP_PORT=8974
+
+EXPOSE 8974
+
+ENTRYPOINT ["openisle-mcp"]

mcp/README.md

@@ -1,37 +1,51 @@
 # OpenIsle MCP Server
 
-This package provides a [Model Context Protocol](https://modelcontextprotocol.io) (MCP) server
-that exposes OpenIsle's search capabilities as MCP tools. The initial release focuses on the
-global search endpoint so the agent ecosystem can retrieve relevant posts, users, tags, and
-other resources.
+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.
 
-## Configuration
+## Features
 
-The server is configured through environment variables (all prefixed with `OPENISLE_MCP_`):
+- ✅ Implements the MCP tooling interface using [FastMCP](https://github.com/modelcontextprotocol/fastmcp).
+- 🔍 Exposes a `search` tool that proxies requests to the existing OpenIsle REST endpoints and normalises the response payload.
+- ⚙️ 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 |
 | --- | --- | --- |
-| `BACKEND_BASE_URL` | `http://springboot:8080` | Base URL of the OpenIsle backend. |
-| `PORT` | `8085` | TCP port when running with the `streamable-http` transport. |
-| `HOST` | `0.0.0.0` | Interface to bind when serving HTTP. |
-| `TRANSPORT` | `streamable-http` | Transport to use (`stdio`, `sse`, or `streamable-http`). |
-| `REQUEST_TIMEOUT` | `10.0` | Timeout (seconds) for backend HTTP requests. |
+| `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. |
 
-## Running locally
+## Local development
 
 ```bash
-pip install .
-OPENISLE_MCP_BACKEND_BASE_URL="http://localhost:8080" openisle-mcp
+cd mcp
+python -m venv .venv
+source .venv/bin/activate
+pip install --upgrade pip
+pip install -e .
+OPENISLE_API_BASE_URL=http://localhost:8080 OPENISLE_MCP_TRANSPORT=http openisle-mcp
 ```
 
-By default the server listens on port `8085` and serves MCP over 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`.
 
-## Available tools
+## Docker image
 
-| Tool | Description |
-| --- | --- |
-| `search` | Perform a global search against the OpenIsle backend. |
+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.
 
-The tool returns structured data describing each search hit including highlighted snippets when
-provided by the backend.
+## MCP tool contract
 
+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.

mcp/pyproject.toml

@@ -1,27 +1,30 @@
 [build-system]
-requires = ["hatchling>=1.25"]
+requires = ["hatchling>=1.25.0"]
 build-backend = "hatchling.build"
 
 [project]
 name = "openisle-mcp"
 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"
-authors = [{ name = "OpenIsle", email = "engineering@openisle.example" }]
+license = {text = "MIT"}
+authors = [{name = "OpenIsle Contributors"}]
 requires-python = ">=3.11"
 dependencies = [
-  "mcp>=1.19.0",
-  "httpx>=0.28,<0.29",
-  "pydantic>=2.12,<3",
-  "pydantic-settings>=2.11,<3"
+  "fastmcp>=2.12.5",
+  "httpx>=0.28.1",
+  "pydantic>=2.7",
 ]
 
 [project.scripts]
 openisle-mcp = "openisle_mcp.server:main"
 
-[tool.hatch.build]
+[tool.hatch.build.targets.wheel]
 packages = ["src/openisle_mcp"]
 
-[tool.ruff]
-line-length = 100
-
+[tool.hatch.build.targets.sdist]
+include = [
+  "src/openisle_mcp",
+  "README.md",
+  "pyproject.toml",
+]

mcp/src/openisle_mcp/__init__.py

@@ -1,6 +1,5 @@
 """OpenIsle MCP server package."""
 
-from .config import Settings, get_settings
-
-__all__ = ["Settings", "get_settings"]
+from .server import main
 
+__all__ = ["main"]

mcp/src/openisle_mcp/client.py

@@ -0,0 +1,218 @@
+"""HTTP client wrappers for interacting with the OpenIsle backend."""
+
+from __future__ import annotations
+
+import html
+import re
+from typing import Any, Iterable
+
+import httpx
+
+from .models import NormalizedSearchResult, SearchResponse, SearchScope
+from .settings import Settings
+
+_TAG_RE = re.compile(r"<[^>]+>")
+_WHITESPACE_RE = re.compile(r"\s+")
+
+
+class SearchClient:
+    """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() + "…"
+
+
+def _safe_int(value: Any) -> int | None:
+    try:
+        return int(value)
+    except (TypeError, ValueError):  # pragma: no cover - defensive
+        return None
+
+
+def _safe_str(value: Any) -> str | None:
+    if value is None:
+        return None
+    text = str(value).strip()
+    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 []

mcp/src/openisle_mcp/config.py

@@ -1,52 +0,0 @@
-"""Application configuration helpers for the OpenIsle MCP server."""
-
-from __future__ import annotations
-
-from functools import lru_cache
-from typing import Literal
-
-from pydantic import Field
-from pydantic.networks import AnyHttpUrl
-from pydantic_settings import BaseSettings, SettingsConfigDict
-
-
-class Settings(BaseSettings):
-    """Configuration for the MCP server."""
-
-    backend_base_url: AnyHttpUrl = Field(
-        "http://springboot:8080",
-        description="Base URL for the OpenIsle backend service.",
-    )
-    host: str = Field(
-        "0.0.0.0",
-        description="Host interface to bind when running with HTTP transports.",
-    )
-    port: int = Field(
-        8085,
-        ge=1,
-        le=65535,
-        description="TCP port for HTTP transports.",
-    )
-    transport: Literal["stdio", "sse", "streamable-http"] = Field(
-        "streamable-http",
-        description="MCP transport to use when running the server.",
-    )
-    request_timeout: float = Field(
-        10.0,
-        gt=0,
-        description="Timeout (seconds) for backend search requests.",
-    )
-
-    model_config = SettingsConfigDict(
-        env_prefix="OPENISLE_MCP_",
-        env_file=".env",
-        env_file_encoding="utf-8",
-        case_sensitive=False,
-    )
-
-
-@lru_cache(maxsize=1)
-def get_settings() -> Settings:
-    """Return cached application settings."""
-
-    return Settings()

mcp/src/openisle_mcp/models.py

@@ -0,0 +1,71 @@
+"""Shared models for the OpenIsle MCP server."""
+
+from __future__ import annotations
+
+from enum import Enum
+from typing import Any
+
+from pydantic import BaseModel, Field
+
+
+class SearchScope(str, Enum):
+    """Supported search endpoints."""
+
+    GLOBAL = "global"
+    POSTS = "posts"
+    POSTS_CONTENT = "posts_content"
+    POSTS_TITLE = "posts_title"
+    USERS = "users"
+
+    def __str__(self) -> str:  # pragma: no cover - convenience for logging
+        return self.value
+
+
+class NormalizedSearchResult(BaseModel):
+    """Compact structure returned by the MCP search tool."""
+
+    type: str = Field(description="Entity type, e.g. user, post, comment.")
+    id: int | None = Field(default=None, description="Primary identifier of the entity.")
+    title: str | None = Field(default=None, description="Display title for the result.")
+    subtitle: str | None = Field(default=None, description="Secondary line of context.")
+    snippet: str | None = Field(default=None, description="Short summary of the result.")
+    metadata: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Additional attributes extracted from the API response.",
+    )
+
+    model_config = {
+        "extra": "ignore",
+    }
+
+
+class SearchResponse(BaseModel):
+    """Payload returned to MCP clients."""
+
+    keyword: str
+    scope: SearchScope
+    endpoint: str
+    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 = {
+        "extra": "ignore",
+    }

mcp/src/openisle_mcp/schemas.py

@@ -1,55 +0,0 @@
-"""Pydantic models describing tool inputs and outputs."""
-
-from __future__ import annotations
-
-from typing import Optional
-
-from pydantic import BaseModel, Field, ConfigDict
-
-
-class SearchResultItem(BaseModel):
-    """A single search result entry."""
-
-    type: str = Field(description="Entity type for the result (post, user, tag, etc.).")
-    id: Optional[int] = Field(default=None, description="Identifier of the matched entity.")
-    text: Optional[str] = Field(default=None, description="Primary text associated with the result.")
-    sub_text: Optional[str] = Field(
-        default=None,
-        alias="subText",
-        description="Secondary text, e.g. a username or excerpt.",
-    )
-    extra: Optional[str] = Field(default=None, description="Additional contextual information.")
-    post_id: Optional[int] = Field(
-        default=None,
-        alias="postId",
-        description="Associated post identifier when relevant.",
-    )
-    highlighted_text: Optional[str] = Field(
-        default=None,
-        alias="highlightedText",
-        description="Highlighted snippet of the primary text if available.",
-    )
-    highlighted_sub_text: Optional[str] = Field(
-        default=None,
-        alias="highlightedSubText",
-        description="Highlighted snippet of the secondary text if available.",
-    )
-    highlighted_extra: Optional[str] = Field(
-        default=None,
-        alias="highlightedExtra",
-        description="Highlighted snippet of extra information if available.",
-    )
-
-    model_config = ConfigDict(populate_by_name=True)
-
-
-class SearchResponse(BaseModel):
-    """Structured response returned by the search tool."""
-
-    keyword: str = Field(description="The keyword that was searched.")
-    total: int = Field(description="Total number of matches returned by the backend.")
-    results: list[SearchResultItem] = Field(
-        default_factory=list,
-        description="Ordered collection of search results.",
-    )
-

mcp/src/openisle_mcp/search_client.py

@@ -1,51 +0,0 @@
-"""HTTP client helpers for talking to the OpenIsle backend search endpoints."""
-
-from __future__ import annotations
-
-import json
-from typing import Any
-
-import httpx
-
-
-class SearchClient:
-    """Client for calling the OpenIsle search API."""
-
-    def __init__(self, base_url: str, *, timeout: float = 10.0) -> None:
-        self._base_url = base_url.rstrip("/")
-        self._timeout = timeout
-        self._client: httpx.AsyncClient | None = None
-
-    def _get_client(self) -> httpx.AsyncClient:
-        if self._client is None:
-            self._client = httpx.AsyncClient(base_url=self._base_url, timeout=self._timeout)
-        return self._client
-
-    async def global_search(self, keyword: str) -> list[dict[str, Any]]:
-        """Call the global search endpoint and return the parsed JSON payload."""
-
-        client = self._get_client()
-        response = await client.get(
-            "/api/search/global",
-            params={"keyword": keyword},
-            headers={"Accept": "application/json"},
-        )
-        response.raise_for_status()
-        payload = response.json()
-        if not isinstance(payload, list):
-            formatted = json.dumps(payload, ensure_ascii=False)[:200]
-            raise ValueError(f"Unexpected response format from search endpoint: {formatted}")
-        return [self._validate_entry(entry) for entry in payload]
-
-    async def aclose(self) -> None:
-        """Dispose of the underlying HTTP client."""
-
-        if self._client is not None:
-            await self._client.aclose()
-            self._client = None
-
-    @staticmethod
-    def _validate_entry(entry: Any) -> dict[str, Any]:
-        if not isinstance(entry, dict):
-            raise ValueError(f"Search entry must be an object, got: {type(entry)!r}")
-        return entry

mcp/src/openisle_mcp/server.py

@@ -1,98 +1,95 @@
-"""Entry point for running the OpenIsle MCP server."""
+"""Entrypoint for the OpenIsle MCP server."""
 
 from __future__ import annotations
 
+import os
 from contextlib import asynccontextmanager
-from typing import Annotated
+from typing import Any
 
 import httpx
-from mcp.server.fastmcp import Context, FastMCP
-from pydantic import ValidationError
-from pydantic import Field as PydanticField
+from fastmcp import Context, FastMCP
 
-from .config import get_settings
-from .schemas import SearchResponse, SearchResultItem
-from .search_client import SearchClient
+from .client import SearchClient
+from .models import SearchResponse, SearchScope
+from .settings import Settings
 
-settings = get_settings()
-search_client = SearchClient(
-    str(settings.backend_base_url), timeout=settings.request_timeout
-)
+__all__ = ["main"]
 
 
-@asynccontextmanager
-async def lifespan(_: FastMCP):
-    """Lifecycle hook that disposes shared resources when the server stops."""
+def _create_lifespan(settings: Settings):
+    @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")
 
-    try:
-        yield
-    finally:
-        await search_client.aclose()
+    return lifespan
 
 
-app = FastMCP(
-    name="openisle-mcp",
+_settings = Settings.from_env()
+
+mcp = FastMCP(
+    name="OpenIsle Search",
+    version="0.1.0",
     instructions=(
-        "Use this server to search OpenIsle posts, users, tags, categories, and comments "
-        "via the global search endpoint."
+        "Provides access to OpenIsle search endpoints for retrieving users, posts, "
+        "comments, tags, and categories."
     ),
-    host=settings.host,
-    port=settings.port,
-    lifespan=lifespan,
+    lifespan=_create_lifespan(_settings),
 )
 
 
-@app.tool(
-    name="search",
-    description="Perform a global search across OpenIsle resources.",
-    structured_output=True,
-)
+@mcp.tool("search")
 async def search(
-    keyword: Annotated[str, PydanticField(description="Keyword to search for.")],
+    keyword: str,
+    scope: SearchScope = SearchScope.GLOBAL,
+    limit: int | None = None,
     ctx: Context | None = None,
-) -> SearchResponse:
-    """Call the OpenIsle global search endpoint and return structured results."""
-
-    sanitized = keyword.strip()
-    if not sanitized:
-        raise ValueError("Keyword must not be empty.")
+) -> dict[str, Any]:
+    """Perform a search against the OpenIsle backend."""
 
+    client = _resolve_client(ctx)
     try:
-        raw_results = await search_client.global_search(sanitized)
-    except httpx.HTTPStatusError as exc:  # pragma: no cover - network errors
-        message = (
-            "OpenIsle backend returned HTTP "
-            f"{exc.response.status_code} while searching for '{sanitized}'."
-        )
-        if ctx is not None:
-            await ctx.error(message)
-        raise ValueError(message) from exc
-    except httpx.RequestError as exc:  # pragma: no cover - network errors
-        message = f"Unable to reach OpenIsle backend search service: {exc}."
-        if ctx is not None:
-            await ctx.error(message)
-        raise ValueError(message) from exc
+        response: SearchResponse = await client.search(keyword=keyword, scope=scope, limit=limit)
+    except httpx.HTTPError as exc:
+        message = f"OpenIsle search request failed: {exc}".rstrip()
+        raise RuntimeError(message) from exc
 
-    try:
-        results = [SearchResultItem.model_validate(entry) for entry in raw_results]
-    except ValidationError as exc:
-        message = "Received malformed data from the OpenIsle backend search endpoint."
-        if ctx is not None:
-            await ctx.error(message)
-        raise ValueError(message) from exc
+    payload = response.model_dump()
+    payload["transport"] = {
+        "scope": scope.value,
+        "endpoint": client.endpoint_url(scope),
+    }
+    return payload
 
-    if ctx is not None:
-        await ctx.info(f"Search keyword '{sanitized}' returned {len(results)} results.")
 
-    return SearchResponse(keyword=sanitized, total=len(results), results=results)
+def _resolve_client(ctx: Context | None) -> SearchClient:
+    app = ctx.fastmcp if ctx is not None else mcp
+    client = getattr(app, "_search_client", None)
+    if client is None:
+        raise RuntimeError("Search client is not initialised; lifespan hook not executed")
+    return client
 
 
 def main() -> None:
-    """Run the MCP server using the configured transport."""
+    """CLI entrypoint."""
 
-    app.run(transport=settings.transport)
+    transport = os.getenv("OPENISLE_MCP_TRANSPORT", "stdio").strip().lower()
+    show_banner = os.getenv("OPENISLE_MCP_SHOW_BANNER", "true").lower() in {"1", "true", "yes"}
+    run_kwargs: dict[str, Any] = {"show_banner": show_banner}
+
+    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__":  # pragma: no cover - manual execution
+if __name__ == "__main__":  # pragma: no cover - manual execution guard
     main()
-

mcp/src/openisle_mcp/settings.py

@@ -0,0 +1,102 @@
+"""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("/")