QM: Multiplayer AI Agent Harness for Workplace Collaboration

Repositoryyc-software/qmTool

QM is an open-source agent harness designed for startups and teams. Unlike single-user personal assistants, it combines isolated personal workspaces with collaborative environments across Slack and the web.

Key points

  1. Multiplayer architecture: Separates personal and shared scopes, each equipped with its own memory, files, keychain view, permissions, and durable sandbox.
  2. Unified Slack and web experience: Preserves identity, configurations, and state between Slack channels and the browser interface.
  3. Vendor-agnostic runtime: Driven by engines like Pi, OpenCode, Codex, or Claude Code to prevent lock-in to any single AI provider.
  4. Background automation: Supports scheduled cron jobs, system watchers, and inbound webhooks for unattended execution.
  5. Technical foundation: Built with TypeScript and uses PostgreSQL for persistent sessions, memory, and task queuing.

Why it matters

Standard AI agents are largely built as individual personal assistants, making team-wide deployment complex and error-prone regarding access controls and shared context. QM bridges personal productivity and collaborative workflows through granular scoping.

Analysis

With over 15,000 stars and nearly 1,900 forks, QM shows significant traction and adoption. It directly targets the friction of running agents in workplace settings by cleanly partitioning shared channel contexts from private employee data. Its compatibility with various runtimes such as Claude Code and OpenCode, paired with persistent PostgreSQL storage, makes it a viable tool for startups looking to operationalise AI assistants in Slack.

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Summary generated by AI (Gemini 3.8 Flash, 29 September 2026). It may contain errors – the original source is authoritative.

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