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Memex - Giving Claude a memory MCP Server

@dioniipereyraa

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基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

dioniipereyraa

投稿者

dioniipereyraa

Memex - Giving Claude a memory MCP Server について

One searchable memory of your Claude.ai chats and Claude Code sessions, served over MCP. Local-first MCP server that indexes your full Claude.ai history and your Claude Code / terminal sessions, then exposes them to Claude Code (stdio) and to Claude.ai (remote connector). Hybrid

#memory#productivity#claude#claude-code

Memex - Giving Claude a memory MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "memex": {
      "command": "uvx",
      "args": [
        "--from",
        "memex-chats",
        "memex-mcp"
      ]
    }
  }
}

Memex - Giving Claude a memory MCP 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。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is Memex?

Memex is a local-first MCP server that indexes your Claude.ai chat history and your local Claude Code/terminal sessions, making both searchable from Claude Code (via stdio) and Claude.ai (via a remote MCP connector). It solves the gap between planning on claude.ai and executing in Claude Code—Claude can now pull in past conversations without manual copy-paste.

How to use Memex?

Install Memex with a single command (curl/sh or PowerShell script), which runs memex setup to wire it into Claude Code, install the always-on capture service, and print a pairing token. Then install the Memex Chrome extension, paste the token, and click “Backfill claude.ai history.” For a manual path, clone the repo, run uv sync, then uv run memex ingest (or memex ingest from a pip install). Start the MCP server with uv run memex-mcp and add a .mcp.json config to Claude Code. Searches are also available from the CLI via memex search.

Key features of Memex

  • Hybrid search (vector + FTS5 BM25) across all indexed chats.
  • Live capture via Chrome extension for new claude.ai chats.
  • Local-first: data stored in SQLite + sqlite-vec, no cloud dependency.
  • Embeddings via fastembed (zero-config) or optional local Ollama.
  • Auto-summaries and chat ↔ repo association.
  • One-command cross-platform setup (macOS, Linux, Windows).
  • Remote MCP connector for claude.ai with GitHub OAuth and IP‑level tunnel.

Use cases of Memex

  • Ask Claude Code about a decision discussed only on claude.ai.
  • Search your entire chat history from Claude Code without leaving the terminal.
  • “Find more like this” for a current problem—find_related retrieves semantically related conversations.
  • Backfill and keep claude.ai history indexed while working in Claude Code.
  • Connect from claude.ai web or mobile to the same indexed corpus via a remote MCP connector.

よくある質問

1

Where does my data live?

From a cloned repo, the database and exports stay in `<repo>/data`. From a pip/uvx install, they go to your OS data directory (`~/Library/Application Support/memex` on macOS, `%LOCALAPPDATA%\memex` on Windows, `~/.local/share/memex` elsewhere). Override with `MEMEX_DB_PATH` / `MEMEX_EXPORTS_DIR`.

2

Do I need an API key or Ollama for embeddings?

No. The default uses a quantized 130 MB fastembed model downloaded automatically on first ingest. To use a local Ollama instead, set `MEMEX_EMBED_BEDEND=ollama` and pull `nomic-embed-text`.

3

How do I connect Memex to claude.ai as a remote MCP server?

Run `memex serve-remote` and make it publicly reachable (e.g., via Tailscale Funnel). Then create a GitHub OAuth App, restrict access to an allow‑list of GitHub usernames, and paste the server URL into claude.ai’s custom connector setup. One connector works across web, desktop, and mobile.

4

What tools does the MCP server expose?

Four tools: `search_chats`, `get_chat`, `list_recent_chats`, and `find_related`. The same functionality is available from the CLI with `memex search`, `memex stats`, etc.

5

How do I run diagnostics if something isn’t working?

Run `memex doctor`. It checks Python version, database health, embedder, live‑capture server, summarizer config, registered repos, and indexed corpus, reporting OK / WARN / FAIL per check.

コメント

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