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Thread Keeper

@po4erk91

Repository

About 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

Basic information

Category

AI & Agents

Transports

stdio

Publisher

po4erk91

Submitted by

Dmytro Bohdanov

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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 neededβ€”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).

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