Mcp Memory Bank

Name: Mcp Memory Bank
Author: bsmi021

@bsmi021

Mcp Memory Bank について

A powerful, production-ready context management system for Large Language Models (LLMs). Built with ChromaDB and modern embedding technologies, it provides persistent, project-specific memory capabilities that enhance your AI's understanding and response quality.

#mcp #context #mcp-server #modelcontextprotocol

基本情報

カテゴリ

メモリとナレッジ

ライセンス

MIT

ランタイム

node

トランスポート

stdio

公開者

bsmi021

設定

標準の設定はありません

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リポジトリ

ツール

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概要

What is Mcp Memory Bank?

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How to use Mcp Memory Bank?

Deploy using Docker Compose. Run docker-compose up --build -d to build and start the application and its required ChromaDB vector database.

Key features of Mcp Memory Bank

Docker-ready deployment with Docker Compose
Uses ChromaDB as vector database
Configurable embedding model via environment variable
Persistent data volumes for ChromaDB
HTTP API on port 3000
Non-root user inside container

Use cases of Mcp Memory Bank

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FAQ from Mcp Memory Bank

What environment variables are required?

Default environment variables include CHROMADB_URL, TRANSPORT, HTTP_PORT, MCP_MEMBANK_EMBEDDING_MODEL, NODE_ENV, and NODE_OPTIONS. They can be overridden in your environment or in docker-compose.yml.

What is the default embedding model?

The default embedding model is Xenova/all-MiniLM-L6-v2, configurable via MCP_MEMBANK_EMBEDDING_MODEL.

Is ChromaDB data persisted?

Yes, ChromaDB data is persisted in the named Docker volume chromadb-data.

What ports does the application use?

Port 3000 for the main application HTTP API, and port 8000 for ChromaDB.

Does the application run as root?

No, the application runs inside the container as a non-root user.

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