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mcp-servers

Collection of Different MCPs for personal homelab use with LLM Agents.

Repository Structure

This repository uses a branch-per-server approach:

  • main branch: Contains base structure, documentation, and skeleton files
  • feature branches: Each branch implements a specific MCP server (e.g., notes-mcp, metrics-mcp)

Project Structure

mcp-servers/
├── src/
│   └── mcp_server/
│       ├── __init__.py
│       └── server.py          # Base MCP server skeleton
├── Dockerfile                  # Docker image definition
├── docker-compose.yml          # Docker Compose configuration
├── requirements.txt            # Python dependencies
└── README.md                   # This file

Getting Started

Prerequisites

  • Python 3.11+
  • Docker and Docker Compose (for containerized deployment)
  • MCP SDK (pip install mcp)

Local Development

  1. Install dependencies:
pip install -r requirements.txt
  1. Run the server:
python -m src.mcp_server.server

Docker Deployment

  1. Build and run with Docker Compose:
docker-compose up -d
  1. Or build and run manually:
docker build -t mcp-server .
docker run -it mcp-server

Creating a New MCP Server

  1. Create a new branch from main:
git checkout -b feature/your-server-name
  1. Extend the base server in src/mcp_server/server.py:

    • Add your tools in list_tools()
    • Implement tool handlers in call_tool()
    • Add resources/prompts as needed
  2. Update requirements.txt with any additional dependencies

  3. Customize docker-compose.yml and Dockerfile if needed

  4. Update this README with server-specific documentation

Base Server Features

The skeleton server includes:

  • Basic MCP server structure using the MCP SDK
  • Tool registration and handling
  • Docker containerization support
  • Docker Compose orchestration

Environment Variables

Create a .env file (see .env.example for template):

  • VAULT_PATH: Path to data directory (default: /app/data)

Documentation

See docs/ directory for detailed documentation on:

  • MCP protocol overview
  • Server implementation patterns
  • Deployment guides

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Collection of Different MCPs for personal homelab use with LLM Agents

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