@bsmi021
基本信息
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.
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Deploy using Docker Compose. Run docker-compose up --build -d to build and start the application and its required ChromaDB vector database.
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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`.
The default embedding model is `Xenova/all-MiniLM-L6-v2`, configurable via `MCP_MEMBANK_EMBEDDING_MODEL`.
Yes, ChromaDB data is persisted in the named Docker volume `chromadb-data`.
Port 3000 for the main application HTTP API, and port 8000 for ChromaDB.
No, the application runs inside the container as a non-root user.
Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.
The official Semantic-UI-React integration
Shared memory for AI coding agents. Claude Code, Cursor and Codex read your project's decisions, lessons and tasks before they act.
Sooveryn gives Claude Code a team of AI personas that remembers your project. Soov, the partner and team lead, keeps your decisions and how you work in a lasting memory, and finds them again by words and by meaning, from
Person-owned, portable AI memory served over MCP. Your knowledge, preferences, and decisions — captured in one assistant, available in all of them.
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