AutoMem MCP connects AI tools to a persistent memory service, allowing them to remember decisions, patterns, and context across sessions. It supports various MCP-compatible platforms for seamless integration.
From the registry: Graph-vector memory for AI assistants using FalkorDB and Qdrant

$ npx @verygoodplugins/mcp-automem setupPlease install the `mcp-automem` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Run setup** — Guided setup creates .env and prints config Run: `npx @verygoodplugins/mcp-automem setup`
- **AutoMem endpoint** — A running AutoMem backend (local or Railway) (https://github.com/verygoodplugins/automem)
Canonical MCP server config (stdio transport):
- command: `npx`
- args: ["-y","@verygoodplugins/mcp-automem"]
- required environment variables:
- `AUTOMEM_ENDPOINT`: AutoMem backend endpoint URL (example: `http://127.0.0.1:8001`)
- optional environment variables:
- `AUTOMEM_API_KEY`: API key (required for Railway, skip for local) (example: `<your-api-key>`)
Note: Also supports remote HTTP/SSE via sidecar service.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.AUTOMEM_ENDPOINTrequiredThe URL of the AutoMem service endpoint.API_KEYrequiredAPI key for accessing the AutoMem service, required for Railway deployments.AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
MCP Toolbox for Databases enables your agent to connect to your database.
MCP Toolbox for Databases enables your agent to connect to your database.