mcp-memory-bank
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-memory-banksave that my favorite color is blue"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🐳 Running with Docker
This project is fully Docker-ready for easy deployment and local development. The provided Dockerfile and docker-compose.yml set up both the main application and its required ChromaDB vector database.
Requirements
Docker (latest stable)
Docker Compose (v2+ recommended)
Environment Variables
The following environment variables are used by default (can be overridden in your environment or via docker-compose.yml):
CHROMADB_URL=http://chromadb:8000
TRANSPORT=http
HTTP_PORT=3000
MCP_MEMBANK_EMBEDDING_MODEL=Xenova/all-MiniLM-L6-v2
NODE_ENV=production
NODE_OPTIONS=--max-old-space-size=4096Build & Run
To build and start all services:
docker-compose up --build -dThis will:
Build the main TypeScript application (Node.js v22.13.1-slim)
Start the app as
ts-app(listening on port 3000)Start ChromaDB as
chromadb(listening on port 8000)Create a persistent volume for ChromaDB data
Set up a shared Docker network for inter-service communication
Ports
3000: Main application HTTP API (
ts-app)8000: ChromaDB vector database (
chromadb)
Data Persistence
ChromaDB data is persisted in the named Docker volume
chromadb-data.Application data directory (
/app/data) is created and owned by a non-root user inside the container.
Special Notes
The application requires ChromaDB to be available at the URL specified by
CHROMADB_URL(default:http://chromadb:8000).The embedding model can be changed via the
MCP_MEMBANK_EMBEDDING_MODELenvironment variable.If you need to customize environment variables, edit the
docker-compose.ymlor use an.envfile.
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