mcp_client_server.py

#!/usr/bin/env python3
"""
MCP Client Server that connects to Hugging Face Spaces API
This acts as a bridge between Cursor and your Hugging Face Spaces server
"""

import json
import asyncio
import logging
import aiohttp
from typing import Any, Dict, List, Optional
from mcp.server import Server
from mcp.server.models import InitializationOptions
from mcp.server.stdio import stdio_server
from mcp.types import (
    Resource,
    Tool,
    TextContent,
    LoggingLevel
)

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Hugging Face Spaces URL - replace with your actual space URL
HF_SPACE_URL = "https://galcan-mcp-docs-server.hf.space"

# Initialize the MCP server
server = Server("mcp-docs-client")

async def make_request(endpoint: str, method: str = "GET", data: dict = None) -> dict:
    """Make HTTP request to Hugging Face Spaces API"""
    url = f"{HF_SPACE_URL}{endpoint}"
    
    try:
        async with aiohttp.ClientSession() as session:
            if method == "GET":
                async with session.get(url) as response:
                    return await response.json()
            elif method == "POST":
                async with session.post(url, json=data) as response:
                    return await response.json()
    except Exception as e:
        logger.error(f"Request failed: {e}")
        return {"error": str(e)}

@server.list_resources()
async def list_resources() -> List[Resource]:
    """List available documentation resources"""
    try:
        # Get docs from HF Spaces
        response = await make_request("/docs")
        if "error" in response:
            return []
        
        resources = []
        for doc in response.get("documents", []):
            resources.append(Resource(
                uri=f"mcp://docs/{doc.get('id', 'unknown')}",
                name=doc.get('title', 'Untitled'),
                description=doc.get('content', '')[:200] + "..." if len(doc.get('content', '')) > 200 else doc.get('content', ''),
                mimeType="text/plain"
            ))
        
        return resources
    except Exception as e:
        logger.error(f"Error listing resources: {e}")
        return []

@server.read_resource()
async def read_resource(uri: str) -> str:
    """Read a specific documentation resource"""
    try:
        # Extract document ID from URI
        if uri.startswith("mcp://docs/"):
            doc_id = uri.replace("mcp://docs/", "")
            
            # Search for chunks related to this document
            search_response = await make_request("/search", "POST", {
                "query": doc_id,
                "limit": 10
            })
            
            if "error" in search_response:
                return f"Error: {search_response['error']}"
            
            results = search_response.get("results", [])
            if results:
                content = "\n\n".join([result.get("text", "") for result in results])
                return content
            else:
                return f"Document {doc_id} not found"
        
        return "Invalid URI"
    except Exception as e:
        return f"Error reading resource: {e}"

@server.list_tools()
async def list_tools() -> List[Tool]:
    """List available tools"""
    return [
        Tool(
            name="search_docs",
            description="Search through MCP documentation chunks on Hugging Face Spaces",
            inputSchema={
                "type": "object",
                "properties": {
                    "query": {
                        "type": "string",
                        "description": "Search query for MCP documentation"
                    },
                    "limit": {
                        "type": "integer",
                        "description": "Maximum number of results",
                        "default": 5
                    }
                },
                "required": ["query"]
            }
        ),
        Tool(
            name="get_chunk",
            description="Get a specific documentation chunk by ID from Hugging Face Spaces",
            inputSchema={
                "type": "object",
                "properties": {
                    "chunk_id": {
                        "type": "string",
                        "description": "Chunk ID to retrieve"
                    }
                },
                "required": ["chunk_id"]
            }
        ),
        Tool(
            name="list_docs",
            description="List all available documents from Hugging Face Spaces",
            inputSchema={
                "type": "object",
                "properties": {}
            }
        ),
        Tool(
            name="health_check",
            description="Check if the Hugging Face Spaces server is running",
            inputSchema={
                "type": "object",
                "properties": {}
            }
        )
    ]

@server.call_tool()
async def call_tool(name: str, arguments: Dict[str, Any]) -> List[TextContent]:
    """Handle tool calls by forwarding to Hugging Face Spaces"""
    
    if name == "search_docs":
        query = arguments.get("query", "")
        limit = arguments.get("limit", 5)
        
        try:
            response = await make_request("/search", "POST", {
                "query": query,
                "limit": limit
            })
            
            if "error" in response:
                return [TextContent(type="text", text=f"Error: {response['error']}")]
            
            results = response.get("results", [])
            total = response.get("total", 0)
            
            if results:
                response_text = f"Found {total} results for '{query}':\n\n"
                for i, result in enumerate(results, 1):
                    response_text += f"{i}. **{result.get('title', 'Untitled')}**\n"
                    response_text += f"   {result.get('text', '')[:200]}...\n"
                    response_text += f"   Source: {result.get('filename', 'Unknown')}\n"
                    if result.get('score'):
                        response_text += f"   Score: {result['score']}\n"
                    response_text += "\n"
            else:
                response_text = f"No results found for '{query}'"
            
            return [TextContent(type="text", text=response_text)]
            
        except Exception as e:
            return [TextContent(type="text", text=f"Error searching: {e}")]
    
    elif name == "get_chunk":
        chunk_id = arguments.get("chunk_id", "")
        
        try:
            response = await make_request(f"/chunks/{chunk_id}")
            
            if "error" in response:
                return [TextContent(type="text", text=f"Error: {response['error']}")]
            
            if response:
                result_text = f"**{response.get('title', 'Untitled')}**\n\n"
                result_text += f"{response.get('text', '')}\n\n"
                result_text += f"Source: {response.get('filename', 'Unknown')}\n"
                result_text += f"URL: {response.get('url', 'N/A')}"
                return [TextContent(type="text", text=result_text)]
            else:
                return [TextContent(type="text", text=f"Chunk {chunk_id} not found")]
                
        except Exception as e:
            return [TextContent(type="text", text=f"Error getting chunk: {e}")]
    
    elif name == "list_docs":
        try:
            response = await make_request("/docs")
            
            if "error" in response:
                return [TextContent(type="text", text=f"Error: {response['error']}")]
            
            docs = response.get("documents", [])
            if docs:
                response_text = "Available documents:\n\n"
                for doc in docs:
                    response_text += f"- **{doc.get('title', 'Untitled')}**\n"
                    response_text += f"  ID: {doc.get('id', 'Unknown')}\n"
                    response_text += f"  URL: {doc.get('url', 'N/A')}\n\n"
            else:
                response_text = "No documents available"
            
            return [TextContent(type="text", text=response_text)]
            
        except Exception as e:
            return [TextContent(type="text", text=f"Error listing docs: {e}")]
    
    elif name == "health_check":
        try:
            response = await make_request("/")
            
            if "error" in response:
                return [TextContent(type="text", text=f"Server error: {response['error']}")]
            
            status = response.get("status", "unknown")
            chunks_loaded = response.get("chunks_loaded", 0)
            docs_loaded = response.get("docs_loaded", 0)
            
            health_text = f"**Hugging Face Spaces Server Status**\n\n"
            health_text += f"Status: {status}\n"
            health_text += f"Chunks loaded: {chunks_loaded}\n"
            health_text += f"Documents loaded: {docs_loaded}\n"
            health_text += f"Server URL: {HF_SPACE_URL}"
            
            return [TextContent(type="text", text=health_text)]
            
        except Exception as e:
            return [TextContent(type="text", text=f"Health check failed: {e}")]
    
    else:
        return [TextContent(type="text", text=f"Unknown tool: {name}")]

async def main():
    """Main entry point"""
    logger.info(f"Starting MCP client server for {HF_SPACE_URL}")
    
    # Run the server
    async with stdio_server() as (read_stream, write_stream):
        await server.run(
            read_stream,
            write_stream,
            InitializationOptions(
                server_name="mcp-docs-client",
                server_version="1.0.0",
                capabilities=server.get_capabilities(
                    notification_options=None,
                    experimental_capabilities=None
                )
            )
        )

if __name__ == "__main__":
    asyncio.run(main())