by kstevica
Self-hosted framework for orchestrating fleets of specialist AI agents — ensemble reasoning and a full agentic coding pipeline, model-agnostic and local-friendly.
# Add to your Claude Code skills
git clone https://github.com/kstevica/captain-clawLast scanned: 6/30/2026
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}captain-claw is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by kstevica. Self-hosted framework for orchestrating fleets of specialist AI agents — ensemble reasoning and a full agentic coding pipeline, model-agnostic and local-friendly. It has 161 GitHub stars.
Yes. captain-claw passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/kstevica/captain-claw" and add it to your Claude Code skills directory (see the Installation section above).
captain-claw is primarily written in Python. It is open-source under kstevica on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh captain-claw against similar tools.
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Most AI tools give you one agent in a chat box. Captain Claw Flight Deck is a multi-agent command center — spawn specialist teams, run six orchestration modes, ship software with Code (a plan → build → independent-review pipeline), and compose deterministic Flows. Self-hosted, MIT licensed, and works with every major LLM provider (or 100% local with Ollama).
🌐 Website · 🚀 Live Demo · 📖 Docs · 📦 PyPI

A self-hosted framework for orchestrating fleets of specialist AI agents — from ensemble reasoning (six orchestration modes) to a full agentic coding pipeline (plan → independent review → ship). Model-agnostic and local-friendly: connect OpenAI, Anthropic, Google Gemini, DeepSeek, Ollama, or OpenRouter (plus "Sign in with ChatGPT" — no API key), or run 100% local with Ollama. Backed by 48 built-in tools per agent, persistent cross-session memory, and autonomous "dream cycle" cognition.
Describe what you want built. A router sizes the job; big work runs plan → your approval → build → three independent reviewers in parallel → triage → capped fix loop, every phase a git commit in the folder's own repo. Agents query a persistent Code Map (symbols + architecture, git-hash-fresh) instead of re-reading your tree; per-turn token costs are shown in chat; the whole process exports as one auditable Markdown transcript. Works on fresh folders or your existing local repos linked in — on any models you configure, including a cheap implementer with a premium reviewer.
Cursor and Claude Code give you one very good agent that plans, writes, reviews, and tests in a single context. Code splits those roles across independent agents — the reviewer never grades its own homework, QA actually runs the tests — and puts you at the approval gate before anything is built. Self-hosted, model-agnostic, no lock-in. A complete real run (an RTS game with 185 tests, ~$2.50 on DeepSeek) ships in examples/code/. Details in RELEASE_NOTES_0.7.0.md and USAGE.md.
One agent isn't always the answer — and one orchestration strategy never is. Captain Claw ships six distinct modes, each tuned to a different kind of work.
The fifth mode is 💻 Code (above) — a plan-gated, independently-reviewed engineering pipeline. The sixth is Flight Deck itself — spawn, monitor, and coordinate the whole crew from one dashboard.
Captain Claw is MIT licensed and free forever — your data stays on your machine, bring your own keys or run 100% local with Ollama. It's built solo and growing fast, and every star helps another builder discover it. If it looks useful, would you give it a star?
Mrav — small models do real work · the village in first person. A parallel micro agentic runtime runs real tool-using loops on 2–4B models (Gemma 4 E2B/E4B, Qwen3.5 4B) under a hard 8k-token input cap per LLM call — locally via Ollama or in your browser tab via WebGPU. And Iskra's village becomes a place you can enter in first person. Everything opt-in; defaults byte-identical.
micro always means mrav.Iskra — living beings you raise. A new Beings page introduces persistent digital beings with a genome, a token wallet, drives, and a life loop that ticks on its own heartbeat — you parent them through real developmental stages (infant → child → adolescent → adult). Additive and self-contained (a new beings.db auto-creates; needs a Flight Deck restart).