Skip to main content
Glama
main.py4.87 kB
#!/usr/bin/env python3 """ CodeBadger Toolkit Server - Main entry point using FastMCP This is the main entry point for the CodeBadger Toolkit Server that provides static code analysis capabilities through the Model Context Protocol (MCP) using Joern's Code Property Graph. """ import asyncio import logging from contextlib import asynccontextmanager from fastmcp import FastMCP from starlette.responses import JSONResponse from src.config import load_config from src.services import ( CodebaseTracker, GitManager, CPGGenerator, JoernServerClient, JoernServerManager, PortManager, QueryExecutor ) from src.utils import RedisClient, SyncRedisClient, setup_logging from src.tools import register_tools # Version information - bump this when releasing new versions VERSION = "0.3.0-beta" # Global service instances services = {} logger = logging.getLogger(__name__) @asynccontextmanager async def lifespan(mcp: FastMCP): """Startup and shutdown logic for the FastMCP server""" # Load configuration config = load_config("config.yaml") setup_logging(config.server.log_level) logger.info("Starting CodeBadger Toolkit Server") # Ensure required directories exist import os os.makedirs(config.storage.workspace_root, exist_ok=True) os.makedirs("playground/cpgs", exist_ok=True) logger.info("Created required directories") try: # Initialize Redis clients redis_client = RedisClient(config.redis) await redis_client.connect() sync_redis_client = SyncRedisClient(config.redis) sync_redis_client.connect() logger.info("Redis clients connected") # Initialize services services['config'] = config services['redis'] = redis_client services['sync_redis'] = sync_redis_client services['codebase_tracker'] = CodebaseTracker(sync_redis_client) services['git_manager'] = GitManager(config.storage.workspace_root) # Initialize port manager for Joern servers services['port_manager'] = PortManager() # Initialize Joern server manager services['joern_server_manager'] = JoernServerManager( joern_binary_path=config.joern.binary_path ) # Initialize CPG generator (runs Joern CLI directly in container) services['cpg_generator'] = CPGGenerator(config=config, joern_server_manager=services['joern_server_manager']) # Skip initialize() - no Docker needed # Initialize query executor with Joern server manager services['query_executor'] = QueryExecutor(services['joern_server_manager'], config=config.query) # Register MCP tools now that services are initialized register_tools(mcp, services) logger.info("All services initialized") logger.info("CodeBadger Toolkit Server is ready") yield # Shutdown logger.info("Shutting down CodeBadger Toolkit Server") # Close connections await redis_client.close() sync_redis_client.close() logger.info("CodeBadger Toolkit Server shutdown complete") except Exception as e: logger.error(f"Error during server lifecycle: {e}", exc_info=True) raise # Initialize FastMCP server mcp = FastMCP( "CodeBadger Toolkit Server", lifespan=lifespan ) # Note: Tools are registered inside the lifespan function # register_tools(mcp, services) # Health check endpoint @mcp.custom_route("/health", methods=["GET"]) async def health_check(request): """Health check endpoint for monitoring server status""" return JSONResponse({ "status": "healthy", "service": "codebadger-toolkit", "version": VERSION }) # Root endpoint @mcp.custom_route("/", methods=["GET"]) async def root(request): """Root endpoint providing basic server information""" return JSONResponse({ "service": "codebadger-toolkit", "description": "CodeBadger Toolkit for static code analysis using Code Property Graph technology", "version": VERSION, "endpoints": { "health": "/health", "mcp": "/mcp" } }) if __name__ == "__main__": # Run the server with HTTP transport (Streamable HTTP) # Get configuration config_data = load_config("config.yaml") host = config_data.server.host port = config_data.server.port logger.info(f"Starting CodeBadger Toolkit Server with HTTP transport on {host}:{port}") # Use HTTP transport (Streamable HTTP) for production deployment # This enables network accessibility, multiple concurrent clients, # and integration with web infrastructure mcp.run(transport="http", host=host, port=port)

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Lekssays/codebadger-toolkit'

If you have feedback or need assistance with the MCP directory API, please join our Discord server