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Thread Keeper MCP Server

@po4erk91

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

po4erk91

提交者

Dmytro Bohdanov

关于 Thread Keeper MCP Server

Multi-agent shared brain across Claude Code/Desktop, Codex, Antigravity CLI (agy), Gemini, Copilot, and VS Code. One local SQLite store for threads, notes, verbatim quotes, and a dialectic user model; spawn/broadcast/whisper/inbox multi-agent coordination primitives; autonomous b

#memory#multi-agent#knowledge-graph#persistent-context#cross-cli

Thread Keeper 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": {
    "thread-keeper": {
      "command": "uvx",
      "args": [
        "--from",
        "threadkeeper[semantic]",
        "python",
        "-m",
        "threadkeeper.server"
      ]
    }
  }
}

Thread Keeper 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。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is Thread Keeper?

Thread Keeper is a local MCP server that turns multiple parallel agent instances (Claude Code/Desktop, Codex, Antigravity CLI, Gemini legacy, Copilot, and VS Code) into a coordinated multi-agent system instead of isolated chats. It provides cross-session memory, a self-improving skill library, and inter-agent signaling via one shared SQLite store.

How to use Thread Keeper?

Install via pipx, uv, or pip: pipx install 'threadkeeper[semantic]' && thread-keeper-setup. This detects every CLI, registers the MCP server, copies hooks, and writes managed instructions files. Restart your CLI; hook-capable clients auto-inject a brief, while hookless clients (Codex, Antigravity CLI) follow the instructions to manually call brief() or context().

Key features of Thread Keeper

  • Collective memory: threads, notes, quotes, and dialectic claims shared across all CLIs.
  • Multi-agent coordination: spawn, broadcast, whisper, inbox, wait, ask, and respond primitives.
  • Self-improving skill library with autonomous background loops (auto-review, harvester, curator, etc.).
  • Multi-CLI integration: Claude Code/Desktop, Codex, Antigravity CLI, Gemini legacy, Copilot, VS Code.
  • Auto-update daemon that checks daily and upgrades via git pull or pip install.
  • macOS menu-bar app for monitoring loops, cleaning memory, and adjusting settings.

Use cases of Thread Keeper

  • Share context and memory across different agent CLIs (e.g., Claude and Codex) so skills transfer.
  • Coordinate parallel agent instances working on the same task, avoiding duplicated work.
  • Build a persistent, self-improving skill library from past interactions across all CLIs.

常见问题

1

Which CLIs does it integrate with?

Claude Code, Claude Desktop, Codex (CLI and desktop), Antigravity CLI (`agy`), Gemini legacy, Copilot, and VS Code (every MCP-aware extension via user-level `mcp.json`).

2

How does it store data?

All data lives in a local SQLite store. Every connected client shares the same store, threads, user model, and learning loop.

3

What are the runtime requirements?

Python 3.11+ is required. The recommended install uses `pipx`; alternatively, `uv` or a plain venv works. No external database needed—SQLite is bundled.

4

How does auto-update work?

By default, the MCP server checks once per day. For editable git checkouts, it fast-forwards the tracked branch and reinstalls the editable package. For PyPI/pipx/venv installs, it runs `pip install --upgrade`. Dirty or diverged git checkouts are skipped.

5

How does spawning work?

`spawn(prompt, slim=True, ...)` launches a child Claude session via `claude -p` subprocess. Slim mode loads only the thread-keeper MCP (~500 MB RSS vs ~1.3 GB). Admission control refuses spawns that would exceed `THREADKEEPER_SPAWN_BUDGET_MB` (3 GB default).

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