Local MCP memory server with Git storage and semantic search

Local MCP Memory Server with Git Storage and Semantic Search

This tool provides a decentralized, local memory server for MCP agents. It leverages Git for version control and synchronization, eliminating the need for traditional databases. Data is stored in Markdown or JSON files, making it easily accessible and human-readable. The core functionality includes robust semantic search capabilities, allowing agents to retrieve relevant information efficiently based on meaning rather than exact keyword matches.

What it Does

The Local MCP Memory Server acts as a persistent storage and retrieval system for your AI agents. It allows agents to store and recall information in a structured, version-controlled manner. By using Git, it enables collaborative development and ensures data integrity. The semantic search feature is crucial for enabling agents to understand and utilize their memory effectively, going beyond simple string matching to find conceptually related information.

Key Features

• Local Storage: Operates entirely on your local machine, providing privacy and control over your data.
• Git Integration: Utilizes Git for versioning, branching, and merging of memory data, facilitating collaboration and rollback capabilities.
• Database-less Architecture: Stores data in plain Markdown/JSON files, simplifying management and integration.
• Semantic Search: Implements semantic search to retrieve information based on meaning, enhancing agent understanding and recall.
• MCP Compatible: Designed to integrate seamlessly with MCP (Multi-Agent Conversation Protocol) agents.

Who it's For

This tool is specifically designed for AI developers and researchers working with multi-agent systems, particularly those utilizing the MCP framework. It is ideal for:

• Developers building agents that require persistent memory and knowledge recall.
• Teams collaborating on agent development, benefiting from Git-based version control.
• Users who prefer a database-less, file-based approach to data management.
• Anyone looking to enhance their agents' ability to understand and utilize context through semantic search.