MCP.so
ログイン

MCP Memory Server

@sdimitrov

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

作者

sdimitrov

MCP Memory Server について

MCP Memory Server with PostgreSQL and pgvector for long-term memory capabilities

MCP Memory Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

MCP Memory Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Memory Server?

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.

How to use MCP Memory Server?

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.).

Key features of MCP Memory Server

  • PostgreSQL with pgvector for vector similarity search
  • Automatic embedding generation using BERT
  • RESTful API for memory operations (create, search, list)
  • Support for different memory types (learnings, experiences, etc.)
  • Tag-based memory retrieval and confidence scoring
  • Server-Sent Events (SSE) for real-time updates
  • Cursor MCP protocol compatible

Use cases of MCP Memory Server

  • Persisting AI assistant learnings across conversations
  • Semantic search over stored knowledge with vector similarity
  • Real-time monitoring of memory creation and updates
  • Organizing memories by type, source, and tags for structured retrieval

よくある質問

1

What runtimes and databases are required?

PostgreSQL 14+ with the pgvector extension installed, and Node.js 16+.

2

How is data stored and retrieved?

Data is stored in PostgreSQL with vector embeddings (384 dimensions) generated by BERT. Retrieval supports semantic search, tag filtering, and confidence scoring.

3

Does the server support real-time updates?

Yes, via Server-Sent Events (SSE) at the `/mcp/v1/sse` endpoint. Events include `memory.created` and `memory.updated`.

4

How do I connect the server to Cursor?

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.

5

What transport and authentication are used?

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).

コメント

「メモリとナレッジ」の他のコンテンツ