What runtimes and databases are required?
PostgreSQL 14+ with the pgvector extension installed, and Node.js 16+.
@sdimitrov
基本信息
MCP Memory Server with PostgreSQL and pgvector for long-term memory capabilities
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MCP Memory Server implements long-term memory capabilities for AI assistants using mem0 principles, powered by PostgreSQL with pgvector for efficient vector similarity search. It provides RESTful endpoints for memory operations, semantic search, and real-time updates via Server-Sent Events.
Install dependencies with npm install, configure the DATABASE_URL environment variable (requires PostgreSQL 14+ with pgvector extension and Node.js 16+), run npm run prisma:migrate to initialize the database, then start with npm start. To use with Cursor, add the server to ~/.cursor/mcp.json with the node command pointing to src/server.js. Invoke memory operations via HTTP endpoints (POST /mcp/v1/memory, GET /mcp/v1/memory/search, etc.).
PostgreSQL 14+ with the pgvector extension installed, and Node.js 16+.
Data is stored in PostgreSQL with vector embeddings (384 dimensions) generated by BERT. Retrieval supports semantic search, tag filtering, and confidence scoring.
Yes, via Server-Sent Events (SSE) at the `/mcp/v1/sse` endpoint. Events include `memory.created` and `memory.updated`.
Add a `memory` entry to `~/.cursor/mcp.json` with the command `node` and the argument set to the absolute path of `src/server.js` in the installed server directory.
The server communicates over HTTP (REST) with a JSON response format. No authentication mechanism is described; it runs locally with a configurable port (default 3333).

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