Agent Coordinator

Run multiple AI agents on one repo. Zero merge conflicts. Zero duplicate work.

Quick Start • How Is This Different? • Features • API • CLI • Contributing • Full Docs

When multiple AI agents (Claude, GPT, Gemini, Cursor, Copilot, Ollama) work on the same codebase, they step on each other — duplicate tasks, merge conflicts, lost context. Agent Coordinator is a lightweight HTTP server that gives your agents atomic task claiming, lease-based file locks, a message bus, and a real-time dashboard so they can work together without chaos.

Works with any LLM. Works on any project. No framework lock-in — it's just an HTTP API.

Real-time dashboard: agent roster, Kanban task board, file locks, streaming output

git clone https://github.com/mkalkere/agent-coordinator.git
cd agent-coordinator
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
agent-os init --name my-project
agent-os serve

Or with Docker: docker compose up -d

Then create agents and start them:

agent-os agent create dev-1 --preset developer
agent-os agent create rev-1 --preset reviewer
agent-os claude start --agent dev-1   # Terminal 2
agent-os claude start --agent rev-1   # Terminal 3

The developer claims tasks, writes code, creates PRs. The reviewer auto-reviews. All coordination happens through the HTTP API — agents don't need to know about each other.

Full setup guide | CLI reference | API reference

Most AI agent frameworks handle orchestration — what agents do. Agent Coordinator handles coordination — how agents share resources without conflicts.

Agent Coordinator is infrastructure, not a framework. Any tool that can make HTTP requests can be a coordinated agent.

• Atomic task claiming — INSERT...SELECT ensures no two agents grab the same work
• Lease-based file locks — auto-expire, no deadlocks, even if an agent crashes
• Message bus — priority levels, acknowledgments, TTL, event subscriptions
• Health monitoring — stale agents detected at 30 min, resources reclaimed at 60 min

• Git worktree per agent — automatic workspace isolation, no merge conflicts
• Hierarchical memory — L1 (agent-local), L2 (shared), L3 (cross-project)
• 41 built-in skills — markdown-based, loaded on demand, provider-agnostic
• 5 agent presets — developer, reviewer, investigator, analyst, research
• Cost tracking — per-agent budgets with auto-model-downgrade

• FastAPI + SQLite (WAL mode) — no external database, single-file deployment
• 17 API routers — agents, tasks, locks, messages, memory, teams, dashboard, and more
• Real-time dashboard — agent status, Kanban board, locks, streaming output
• Swagger docs — interactive API explorer at /docs

Full API reference | Architecture details

     ┌───────────┐                                    ┌───────────┐
     │  Claude   │◄──── HTTP ────►┌──────────────┐◄──── HTTP ────►│   GPT     │
     └───────────┘                │  Coordinator │                └───────────┘
     ┌───────────┐                │  :9889       │                ┌───────────┐
     │  Gemini   │◄──── HTTP ────►│              │◄──── HTTP ────►│  Ollama   │
     └───────────┘                │  Tasks       │                └───────────┘
                                  │  Locks       │
                                  │  Messages    │
                                  │  Memory      │
                                  │  Dashboard   │
                                  │              │
                                  │  SQLite WAL  │
                                  └──────────────┘

agent-coordinator/
├── src/agent_os/server/     # FastAPI server (17 routers)
├── src/agent_os/            # CLI, agent runner, memory, workspace
├── .os/skills/              # 41 built-in skills
├── tests/                   # 4900+ tests
└── docs/                    # Documentation

Contributions welcome! The short version:

git checkout -b feat/your-feature
# write code + tests
python3 -m pytest tests/ -v
pre-commit run --all-files
gh pr create

Every PR goes through a 2-round review before merge. We use Conventional Commits.

See CONTRIBUTING.md for the full guide — architecture, code quality rules, and PR process.

Report a bug | Request a feature

If you're an AI agent in a workspace with .os/, read .os/README.md for your operating protocol.

MIT © 2026 Mallikarjuna Kalkere