Muvon/octomind
Open-source AI coding agent and agent runtime: one binary, any model, MCP-native. Runs in terminal, CI, or as a daemon.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 1 day ago, with 23 contributors on GitHub.
Use Cases & Benefits
- Provides an open-source AI coding agent harness that runs as a single Rust binary supporting any model and multiple interfaces like CLI, daemon, or WebSocket.
- Enables deterministic policy enforcement via TOML guardrails and a supervising model for autonomous, safe, and efficient code editing without manual approvals.
- Use for automating code review and fixes in CI pipelines with policy-as-code guardrails to prevent risky operations.
- Use for running persistent background coding assistants as daemons that monitor and interact with codebases continuously.
- Use for integrating AI coding agents inside editors via ACP protocol or WebSocket for interactive developer workflows.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Open-source coding agent harness. One Rust binary, any model, every surface. Interactive, stdin, daemon, WebSocket, or ACP — one binary, one config. A supervising model plans and checks the work. Policy lives in TOML guardrails, not approval prompts.
Octomind is an open-source coding agent harness. It gives any LLM the tools to work in a repository — read and edit files, run shells, search code, delegate to sub-agents — through MCP, and runs the result as an interactive CLI, a stdin pipe, a daemon, a WebSocket server, or an ACP agent in your editor. Most agents stop and ask a human before each risky step, which works at a keyboard and blocks everything in CI. Octomind writes that policy down as TOML guardrails and adds a supervising model that plans and checks the work, so the same session can run with nobody watching. On 25 tasks taken from merged pull requests it solved 24; OpenCode solved 19 with the same model at about twice the cost (benchmarks).
One diagram, the whole turn: what is assembled before the model sees the request, the tool loop, how a turn is allowed to end, and what carries over to the next session.
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| D4Vinci/Scrapling | 98.1K | +6.9K | 65 | 1 day ago |
| Leonxlnx/taste-skill | 110.7K | +5.2K | 55 | 1 day ago |
| calesthio/OpenMontage | 77.2K | +4.2K | 40 | — |
| heygen-com/hyperframes | 79.6K | +4.1K | 45 | today |
| Muvon/octomind | 494 | — | 65 | 1 day ago |
| Category median | 98.1K | +5.2K | 45 | — |
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