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Optimized Memory MCP Server v2

Optimized Memory MCP Server v2

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github.com/AgentWongMemory & Knowledge1Updated 95w ago
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About Optimized Memory MCP Server v2

Optimized Memory MCP Server v2 is a Python MCP server for memory management and infrastructure tracking, including entity and infrastructure data workflows with Claude Desktop. It stores data persistently in SQLite; the project is archived, and the README notes specification issues that led to looping behavior.

Key features

  1. 01SQLite persistent storage
  2. 02Entity and relationship management
  3. 03Provider and Ansible collection tracking
  4. 04Version tracking and full-text search
  5. 05Infrastructure analysis tools
  6. 06Error handling and resource cleanup

Use cases

  1. 01Persist infrastructure entities and relationships
  2. 02Record observations and manage providers
  3. 03Track Ansible collections and versions
  4. 04Search and analyze infrastructure data

MCP support

The MCP server exposes resources for entities, providers, Ansible collections, and versions, along with tools for entity management, observation tracking, and infrastructure analysis. The README states compatibility with Claude Desktop.

#mcp#server#claude-ai#mcp-server#ai#python

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "AgentWong_optimized-memory-mcp-serverv2": {
      "command": "uvx",
      "args": [
        "run"
      ]
    }
  }
}
Run commanduvx run

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypirun

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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This project has been archived due to faulty project specifications and AI direction that led to endless looping behavior.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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.