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2025-01-06

This is a personal project to test Claude AI's ability to self-write an MCP Server code for its own use.

3 years

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Optimized Memory MCP Server v2

A high-performance Python-based Model Context Protocol (MCP) server implementation optimized for Claude Desktop integration. This server provides efficient memory management and robust infrastructure component tracking capabilities.

[!CAUTION] This project has been archived due to faulty project specifications and AI direction that led to endless looping behavior.

Overview

This MCP server implementation focuses on:

  • Efficient memory management for large-scale infrastructure tracking
  • Comprehensive resource and tool implementations following MCP patterns
  • Full Claude Desktop compatibility
  • SQLite-based persistent storage with connection pooling
  • Robust error handling and resource cleanup

Features

  • MCP Resources

    • Entity management (listing, retrieval, relationships)
    • Provider resource tracking
    • Ansible collection management
    • Version tracking
    • Full-text search capabilities
  • MCP Tools

    • Entity creation and management
    • Observation tracking
    • Provider registration
    • Ansible module integration
    • Infrastructure analysis tools
  • Core Components

    • FastMCP server implementation
    • SQLite database with connection pooling
    • Comprehensive error handling
    • Automatic resource cleanup
    • Extensive logging

Project Structure

.
├── src/
│   ├── resources/          # MCP resource implementations
│   ├── tools/             # MCP tool implementations
│   ├── db/                # Database management
│   ├── utils/             # Utility functions
│   └── server.py          # Main server implementation
├── tests/
│   ├── resources/         # Resource tests
│   ├── tools/             # Tool tests
│   └── integration/       # Integration tests
├── docs/                  # Documentation
├── migrations/            # Database migrations
└── requirements/          # Project dependencies

Requirements

  • Python 3.13.1 or higher
  • SQLite 3.x
  • uvx server

Quick Start

See our Environment Setup Guide for detailed installation instructions.

Key steps:

  1. Clone and setup Python environment
  2. Install dependencies: pip install -r requirements.txt
  3. Configure database: export DATABASE_URL=sqlite:///path/to/db.db
  4. Initialize database: alembic upgrade head
  5. Start server: uvx run python -m src.main

Usage

  1. Start the server:

    uvx run python -m src.main
    
  2. Configure Claude Desktop:

    • Set MCP server URL to http://localhost:8000
    • Enable MCP protocol in Claude settings
  3. Verify connection:

    curl http://localhost:8000/health
    

Development Setup

  1. Install development dependencies:

    pip install -r requirements-dev.txt
    
  2. Set up pre-commit hooks:

    pre-commit install
    
  3. Run tests:

    pytest
    
  4. Check code quality:

    flake8
    mypy .
    

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes following our conventions
  4. Run tests and linting
  5. Submit a pull request

Documentation

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Claude Desktop team for MCP protocol specifications
  • Contributors to the FastMCP library
  • SQLAlchemy team for database tooling

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    Reviews

    4 (1)
    Avatar
    user_YvTrET1I
    2025-04-15

    simctl-mcp by ambar is an excellent tool for anyone working with the Mobile Core Platform. The user interface is intuitive, and the functionality is robust, making it perfect for both beginners and advanced users. Highly recommend visiting the product link to discover its full potential: https://mcp.so/server/simctl-mcp/ambar.