A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
410 ★ · Keesan12/martin-loop · read from the repository page · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 410 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository Keesan12/martin-loop;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
**Give coding agents more work. Watch them less. Ship more.** MartinLoop lets you give coding agents real software jobs without babysitting every step. Your coding agent still writes the code. MartinLoop keeps the job focused, bounded, and accountable — with limits, stop conditions, verification, recovery, and a clear outcome when the run ends. **Trust your coding agents with real work.** Built from thousands of agent runs where the problem was not just intelligence — it was whether you could give the agent a real job and confidently walk away. **Measure your loop tax:** npx -y martin-loop@latest audit **Get started:** npx -y martin-loop@latest start **Try the demo:** npx -y martin-loop@latest demo MartinLoop is part of the NVIDIA Inception program. Start Here **Audit first** — run npx -y martin-loop@latest audit to see how much API-equivalent Claude Code spend went into fix-and-retry loops. Add --offline for zero network access or --share for a shareable summary. **Install / onboard** — run npx -y martin-loop@latest start, or install it globally with npm install -g martin-loop@latest. **Governed run** — define an objective, verifier, budget, and iteration cap with martin run. **Verifier** — completion requires fresh verifier evidence bound to the active run and workspace. A configured verifier proves only the checks it runs; VERIFIED is not a claim that the code is bug-free or automatically safe to merge. **Budget** — set a hard spend ceiling with --budget-usd and an attempt ceiling with --max-iterations. **Receipts** — inspect the latest result with martin dossier --latest and validate stored integrity with martin runs verify --latest. **Hosted sync (optional)** — governed work is local-first. Configure MARTIN_API_TOKEN and MARTIN_TELEMETRY_ENDPOINT, then use martin sync status and martin sync flush to send preserved evidence to a dashboard later. See the quickstart. **MCP** — install @martinloop/mcp@latest in a supported host or generate host configuration with martin mcp print-config. **Documentation** — continue with the quickstart, CLI reference, or MCP setup. When --model is provided, MartinLoop passes it through unchanged. Without --model, the authenticated host runtime chooses its own default. MartinLoop does not inject a hidden fallback model. For AI Agents MartinLoop is the system around the coding job. The coding agent still writes the code. MartinLoop keeps the job, limits, verification, recovery, outcome, and history consistent around the work. Use MartinLoop when a coding task needs: - clear job and success criteria - preflight readiness before agent spend - hard budget and iteration limits - allowed or denied edit scope - controlled retries and stop conditions - independent verifier commands - recovery and rollback evidence - a finite completion decision - run receipts, dossiers, history, failure classification, and post-run analysis - one consistent workflow across supported coding-agent runtimes Canonical lifecycle: The product-level flow is **Definition of Done -> Controlled Run -> Verified Handoff**. For machine-readable context start with llms.txt, llms-full.txt, and MartinLoop for AI Agents. One System Around the Run Teams should not need to stitch together a separate script or point tool for every part of coding-agent execution. MartinLoop connects the control path around the agent from preflight through post-run evidence. | Stage | MartinLoop role | | --- | --- | | Define | Capture the objective, verifier, budget, scope, and finish line. | | Preflight | Check readiness and required workflow evidence before agent spend. | | Control | Enforce budgets, attempts, path boundaries, policy, and stop conditions while the coding agent works. | | Verify | Run configured checks and bind the evidence to the active run and workspace. | | Recover | Preserve recovery and rollback state when another attempt or human review is required. | | Prove | Produce the authoritative VERIFIED, STOPPED, or NEEDS REVIEW handoff plus receipts. | | Analyze | Inspect run history, cost provenance, failure classes, dossiers, and shareable evidence after execution. | MartinLoop does not replace Git, GitHub, CI, dedicated security scanners, observability platforms, code review, or the coding agent itself. It gives those workflows one governed execution record to inspect.