Optimized Memory MCP Server v2
@AgentWong
About Optimized Memory MCP Server v2
This is a personal project to test Claude AI's ability to self-write an MCP Server code for its own use.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"optimized-memory-mcp-serverv2": {
"command": "uvx",
"args": [
"run",
"python",
"-m",
"src.main"
]
}
}
}Tools
No tools detected
Fetch the live tool list by running this server in a temporary sandbox using the button above.
Overview
What is Optimized Memory MCP Server v2?
Optimized Memory MCP Server v2 is a high-performance Python-based Model Context Protocol (MCP) server implementation optimized for Claude Desktop integration. It provides efficient memory management and robust infrastructure component tracking capabilities, using SQLite for persistent storage with connection pooling.
How to use Optimized Memory MCP Server v2?
Clone the repository, set up a Python environment (Python 3.13.1+), install dependencies with pip install -r requirements.txt, configure the database URL via the DATABASE_URL environment variable, run database migrations with alembic upgrade head, then start the server with uvx run python -m src.main. In Claude Desktop, set the MCP server URL to http://localhost:8000 and enable the MCP protocol in settings.
Key features of Optimized Memory MCP Server v2
- MCP resources for entity, provider, and Ansible collection management
- MCP tools for entity creation, observation, and provider registration
- Full-text search across tracked infrastructure components
- SQLite database with connection pooling and automatic cleanup
- Comprehensive error handling and extensive logging
- Full Claude Desktop compatibility via FastMCP
Use cases of Optimized Memory MCP Server v2
- Tracking infrastructure components and their relationships in a centralized store
- Managing Ansible collections and provider resources through MCP tools
- Performing full-text search on entities, observations, and metadata
- Integrating with Claude Desktop for AI-assisted infrastructure analysis
FAQ from Optimized Memory MCP Server v2
What are the runtime requirements?
Python 3.13.1 or higher, SQLite 3.x, and the uvx server. Dependencies are listed in requirements.txt.
How do I start the server?
Run uvx run python -m src.main after installing dependencies, configuring the database URL, and applying migrations with alembic upgrade head.
How do I connect Claude Desktop to this server?
Set the MCP server URL in Claude Desktop to http://localhost:8000 and enable the MCP protocol in Claude settings. Verify the connection with curl http://localhost:8000/health.
How is data stored?
Data is stored persistently in a SQLite database. The database URL is configured via the DATABASE_URL environment variable (e.g., sqlite:///path/to/db.db). Migrations are managed with Alembic.
Is this project still maintained?
No. The README indicates the project has been archived due to faulty project specifications and AI direction that led to endless looping behavior.
Frequently asked questions
What are the runtime requirements?
Python 3.13.1 or higher, SQLite 3.x, and the uvx server. Dependencies are listed in `requirements.txt`.
How do I start the server?
Run `uvx run python -m src.main` after installing dependencies, configuring the database URL, and applying migrations with `alembic upgrade head`.
How do I connect Claude Desktop to this server?
Set the MCP server URL in Claude Desktop to `http://localhost:8000` and enable the MCP protocol in Claude settings. Verify the connection with `curl http://localhost:8000/health`.
How is data stored?
Data is stored persistently in a SQLite database. The database URL is configured via the `DATABASE_URL` environment variable (e.g., `sqlite:///path/to/db.db`). Migrations are managed with Alembic.
Is this project still maintained?
No. The README indicates the project has been archived due to faulty project specifications and AI direction that led to endless looping behavior.
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