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This repository serves as a curated roster of MCP (Model Context Protocol) servers, illustrating a variety of capabilities and SDK integrations rather than hosting a single executable MCP server itself. It highlights reference servers and production-ready implementations that demonstrate MCP features such as prompts, tools, memory, file access, code repositories, and more. To explore or experiment, browse the referenced server directories and external links to understand how different MCP servers implement tool use, memory, retrieval, and command execution within the MCP framework. You can click through the links to run or inspect each server in its native environment and study how the TypeScript and Python SDKs are wired into MCP endpoints.

Prerequisites:

• Basic familiarity with git and a command line.
• Node.js and npm for Node-based servers, Python for Python-based servers, and Docker if you prefer containerized runs.

Step-by-step:

1. Browse the repository to identify a specific MCP server you want to run (e.g., Everything, Fetch, Filesystem, Git).
2. Open the target server directory or external repository link to read its specific installation instructions.
3. Install dependencies for the chosen server:
   • Node.js server: clone the repo, run npm install in the server directory, then start the server (e.g., npm run start or node path/to/server.js).
   • Python server: create a virtual environment, install requirements, and run the server according to its docs (e.g., python -m <module> or python path/to/server.py).
   • Docker: pull and run the provided image if available (e.g., docker run -i image-name).
4. Configure any required environment variables as documented in the specific server’s README (API keys, endpoints, ports, etc.).
5. Start the server and verify by calling its MCP endpoints or using the SDK to interact with it.
6. If you want a local testing setup, consider using the SDKs referenced (TypeScript SDK or Python SDK) to connect to the running MCP server and execute prompts, prompts-with-tools, and memory operations.

Notes and tips:

• This repository is a catalog. Each server typically has its own setup and configuration requirements; always check the individual server’s README for precise instructions.
• Some servers expose tools and memory components; ensure you understand the access controls and security implications when enabling tool usage or filesystem operations.
• When running multiple MCP servers locally, consider using distinct ports and environment configurations to avoid conflicts.
• If you plan to integrate with the TypeScript or Python SDKs, ensure the SDK version aligns with the server’s MCP protocol version.
• For production deployments, prefer containerized runs (Docker) or platform-specific deployment guides provided by the server maintainers.