Memo MCP Server

@jagoff

代码仓库

基本信息

分类

记忆与知识

传输方式

stdio

作者

jagoff

提交者

Fer F.

关于 Memo MCP Server

memo is a local-first, long-term semantic memory for AI coding agents (Claude Code, Cursor, Cline, Codex). Runs fully offline with in-process embeddings — MLX on Apple Silicon or CPU sentence-transformers on Linux/Docker — and a sqlite-vec + BM25 hybrid retrieval pipeline with re

#memory #rag #mcp#mlx#local-first #embeddings#sqlite-vec#obsidian #agents #knowledge-graph

Memo MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "memo": {
      "command": "memo-mcp"
    }
  }
}

Memo MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Memo?

Memo is a local-first, long-term semantic memory server for AI coding agents (Claude Code, Cursor, Cline, Codex). It runs fully offline with in-process embeddings and uses a sqlite-vec + BM25 hybrid retrieval pipeline with reranking.

How to use Memo?

Install via pipx install mlx-memo. Use the memo CLI for command-line interaction, or run the memo-mcp MCP server to connect with compatible AI coding tools.

Key features of Memo

Local-first and fully offline, no cloud or API keys required.
Uses MLX (Apple Silicon) or CPU sentence-transformers (Linux/Docker) for embeddings.
Hybrid retrieval with sqlite-vec + BM25 and reranking.
Markdown files on disk are the source of truth; SQLite index is rebuildable.
Recall hook auto-injects relevant memories into every prompt.
Includes a knowledge graph, temporal/time-machine queries, contradiction detection, and nightly synthesis.

Use cases of Memo

Provide persistent semantic memory for AI coding agents across sessions.
Enable offline retrieval of past context, decisions, and code snippets.
Detect contradictions in project documentation or agent memory.
Build a searchable knowledge graph from markdown notes.

常见问题

What makes Memo local-first?

All processing happens on your machine. Embeddings are computed in-process using MLX or sentence-transformers, and the SQLite index is stored locally. No data leaves your environment.

What are the runtime requirements?

On Apple Silicon, Memo uses ML

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