model-context-protocol-resources

This repository provides a collection of MCP (Model Context Protocol) resources, guides, utilities, and a variety of server implementations that demonstrate how to expose tools, data sources, and capabilities to LLM clients. You can explore the included guides to learn how MCP servers are structured, how they expose capabilities, and how to integrate them with MCP clients. The repository also features templates and examples (such as the MCP TypeScript Template) to help you build and test your own servers. Use the provided guides to understand server development patterns, authentication and validation practices, and how to compose complex tools into a cohesive MCP ecosystem. When you want to trial a server, refer to the specific server’s README or docs within this repository to learn its endpoints, capabilities, and configuration options, then run it in your preferred environment to connect it to an MCP client.

Typical workflows include selecting a server example (e.g., filesystem, Git, PubMed, or other domain-specific servers), running the server locally or in a container, and then configuring an MCP client to query or invoke the server’s capabilities. The MCP servers expose a standardized interface for discovery, tool calls, and data retrieval, enabling LLMs to interact with external data sources and utilities in a secure and structured way.

Prerequisites:

• A modern runtime environment (Node.js, Python, Java, or container tooling) depending on the server you choose to run.
• Git to clone the repository.
• Optional: Docker if you plan to run servers in containers.

Step-by-step:

1. Fork or clone the repository: git clone https://github.com/cyanheads/cyanheads-model-context-protocol-resources.git cd cyanheads-model-context-protocol-resources

2. Review the Guides and Servers sections to identify a specific server example you want to run (e.g., filesystem-mcp-server, git-mcp-server, pubmed-mcp-server).

3. Follow the installation instructions for the chosen server within its dedicated directory. Common patterns you may encounter:

   • Node/TypeScript server:

     • cd path/to/server
     • npm install
     • npm run build (if applicable)
     • npm start (or a provided start script)

   • Python server:

     • cd path/to/server
     • python -m venv venv
     • sources/venv/bin/activate (Unix) or venv\Scripts\activate (Windows)
     • pip install -r requirements.txt
     • python main.py

   • Docker-based server:

     • Ensure Docker is running
     • docker compose up -d (or docker run with appropriate arguments)

4. Configure environment variables if required by the server (e.g., API keys, database connection strings). Create a .env file or export variables as needed.

5. Connect an MCP client to the running server following the server’s documentation to validate discovery, tool invocation, and data retrieval.

6. Use the server templates or guides to extend or customize capabilities as needed.

Tips and common considerations:

• Check each server’s README for required environment variables (e.g., API keys or data source credentials) and how to securely pass them.
• If you run servers locally, consider using Docker or a virtual environment to isolate dependencies.
• The MCP concept emphasizes standardized interfaces for discovery, invocation, and response handling. Ensure your client adheres to these patterns for interoperability.
• When exploring resources, start with smaller, well-documented servers (like filesystem or Git helpers) before attempting domain-specific data sources.
• If you encounter issues with tool discovery, verify the server is reachable at the expected host/port from your MCP client and that any authentication requirements are satisfied.