MCP Memory Bank Server
by bsmi021
MCP Memory Bank Server is a context management system for Large Language Models (LLMs). It provides persistent, project-specific memory capabilities that enhance your AI's understanding and response quality.
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What is MCP Memory Bank Server?
MCP Memory Bank Server is a powerful context management system designed for Large Language Models (LLMs). It leverages ChromaDB and embedding technologies to provide persistent, project-specific memory, improving AI understanding and response quality.
How to use MCP Memory Bank Server?
To use the MCP Memory Bank Server, start by cloning the repository and setting up the required environment (Node.js, npm, Docker). Use the provided one-command setup script to install dependencies and run the server in development mode. Utilize the API endpoints for project and content management, such as creating projects, updating files, and performing semantic or keyword searches. Configure environment variables for ChromaDB URL and embedding model.
Key features of MCP Memory Bank Server
High Performance: Optimized vector storage with ChromaDB
Project Isolation: Separate context spaces for different projects
Smart Search: Both semantic and keyword-based search capabilities
Real-time Updates: Dynamic content management with automatic chunking
Precise Recall: Advanced embedding generation via @xenova/transformers
Easy Deployment: Docker-ready with persistent storage
Use cases of MCP Memory Bank Server
Enhancing LLM understanding in project-specific contexts
Providing persistent memory for AI applications
Enabling semantic search and retrieval of relevant information
Managing and updating content dynamically for AI models
FAQ from MCP Memory Bank Server
How do I create a new project?
How do I create a new project?
Use the memoryBank_createProject API call to create an isolated project space.
How do I store or update content in a project?
How do I store or update content in a project?
Use the memoryBank_updateFile API call to store or update content with automatic chunking.
How do I perform a search within a project's memory?
How do I perform a search within a project's memory?
Use the memoryBank_search API call to perform semantic or keyword searches.
What do I do if I encounter ChromaDB connection issues?
What do I do if I encounter ChromaDB connection issues?
Check if the ChromaDB container is running using docker ps | grep chroma. If it's not running, restart it using docker-compose restart.
How can I contribute to the project?
How can I contribute to the project?
Fork the repository, create a feature branch, commit your changes, push to the branch, and open a pull request.