Thread Keeper

Name: Thread Keeper
Author: po4erk91

@po4erk91

关于 Thread Keeper

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

基本信息

分类

AI 与智能体

传输方式

stdio

发布者

po4erk91

提交者

Dmytro Bohdanov

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"
      ]
    }
  }
}

工具

未检测到工具

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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.

FAQ from Thread Keeper

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).

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.

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.

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.

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).