MCP Server Validator

MCP is an open standard by Anthropic that lets LLM applications connect to external data sources and tools. An MCP server exposes 'tools', 'resources', and 'prompts' that AI assistants can use. Think of it as a plugin system for LLMs — a server can provide database access, file operations, API integrations, or any other capability.

MCP servers are configured in a JSON file (usually claude_desktop_config.json or mcp.json). Each server entry has a name, command to run the server, args, and optional env variables. Example: {"mcpServers": {"filesystem": {"command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/files"]}}}. Claude Desktop, Cursor, and other MCP clients load this config.

stdio transport runs the MCP server as a child process and communicates over stdin/stdout — best for local servers. SSE (Server-Sent Events) transport connects to an HTTP server via GET for events and POST for requests — best for remote or already-running servers. stdio is simpler for local development; SSE enables multi-client scenarios.

Use the MCP Inspector: npx @modelcontextprotocol/inspector. It connects to your server and shows all available tools, resources, and prompts, and lets you invoke them directly. For Claude Desktop, check the logs in ~/Library/Logs/Claude/ (Mac) or %APPDATA%/Claude/logs/ (Windows). Errors in the server startup are visible there.

Be careful with filesystem access — limit to specific directories. Never expose secrets in the MCP config file (use env vars instead). For remote SSE servers, use authentication headers. Review tool descriptions carefully — they become part of the LLM context and could influence behavior. Only connect to trusted MCP servers.