This repository provides practical resources, guides, and example server implementations for the Model Context Protocol (MCP), an emerging standard for unifying AI agent interactions with external data and tools. It empowers developers to build extensible AI capabilities by offering a standardized, modular interface, akin to USB-C for AI integration.

How It Works

MCP establishes a universal protocol enabling AI applications (clients) to discover and interact with external data sources and tools (servers). This repository showcases various server implementations (e.g., file system, Git, PubMed) and client development guides, demonstrating how MCP standardizes communication, enhances AI functionality, and promotes modular, reusable components.

Quick Start & Requirements

Getting started involves exploring the provided guides (Client/Server Development) and selecting a specific server implementation from the repository. The mcp-ts-template offers a production-ready starting point for building MCP servers and clients. Specific prerequisites depend on the chosen server; official MCP resources and SDKs (TypeScript, Python, etc.) are linked for further development.

Highlighted Details

• Diverse Server Ecosystem: Features numerous MCP server examples, including integrations with Git, GitHub, file systems, ClinicalTrials.gov, Obsidian, Perplexity, PubMed, and a declarative workflow engine.
• TypeScript Template: Offers a robust, production-ready template for developing MCP servers and clients, emphasizing type safety and essential utilities.
• MCP Reporter Utility: A tool for generating comprehensive capability reports for MCP servers, aiding ecosystem understanding and integration.
• In-depth Guides: Provides detailed documentation for both MCP client and server development, covering architecture, protocol specifics, security, and advanced features.

Maintenance & Community

Developed independently by "cyanheads," the project welcomes questions and feedback. While not officially affiliated with the Model Context Protocol organization, it actively links to and acknowledges official resources and community discussions.

Licensing & Compatibility

The license for this specific repository's content is not explicitly stated. Compatibility is designed for integration within AI applications and LLM workflows, with specific requirements dictated by individual server implementations.

Limitations & Caveats

The "MCP Client Development Guide" requires updates for recent specification changes. The project reflects ongoing exploration and development, and it is not officially affiliated with the Model Context Protocol organization.