Martin Loop

Name: Martin Loop
Author: Keesan12

by Keesan12version 0.9.0i★ –iRuns on your computer

Registry nameio.github.Keesan12/martin-loop

Install

Overview

Description from the maker (original English)

One system around coding agents to run, verify, recover, and hand off software work.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "martin-loop": {
      "command": "npx",
      "args": [
        "-y",
        "@martinloop/mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add martin-loop -- npx -y @martinloop/mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "martin-loop": {
      "command": "npx",
      "args": [
        "-y",
        "@martinloop/mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "martin-loop": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@martinloop/mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account Keesan12, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32417 servers in this category
Published to the registry more recently than 92% of the other 32417 servers in this category
Basic checks equal to or better than 100% of the other 32417 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Martin Loop safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.9.0) reached the registry 2 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, FOGA node

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

MartinLoop

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:

DEFINE

-> PREFLIGHT -> CONTROL -> VERIFY -> RECOVER -> PROVE -> ANALYZE

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.

Change the worker. Keep the job.

MartinLoop is model-agnostic by design. The job, limits, verification, recovery, and outcome are separate from the worker underneath.

Native coding-agent CLIs and OpenAI-compatible model runtimes use different execution paths, so MartinLoop only describes a worker as fully supported when that execution path has been publicly released and validated.

Why MartinLoop

AI coding agents can create more software than ever. The problem is trusting them with bigger jobs without turning yourself into their full-time manager.

Agents drift. They retry. They break unrelated things. They say "done" too early. And a run that was supposed to save time can create even more work to review.

MartinLoop keeps the job accountable outside the agent itself: clear boundaries, hard limits, configured checks, recovery information, and an explicit outcome.

The goal is simple:

Give the agent more responsibility without giving it unlimited freedom.

Why Teams Adopt MartinLoop

Less babysitting — give agents larger jobs without watching every step.
Clear boundaries — keep scope, attempts, and spend inside the limits you set.
Checks before "done" — configured verification decides whether the evidence passed.
Understand failures — know why the run stopped instead of digging through logs.
Recover cleanly — preserve enough evidence to retry, repair, roll back, or hand off.
One workflow across agents — keep the job consistent as the worker underneath changes.

More software. Less supervision.

See Your Loop Tax

Before changing your workflow, measure it:

npx -y martin-loop@0.9.0 audit

MartinLoop reads Claude Code session history locally and reports how much API-equivalent agent spend happened inside fix-and-retry loops, how often verifier commands failed, the longest retry chain, and sessions that ended red. Session contents stay local. Use --offline to disable even the public pricing lookup, and --share to create a screenshot-ready SVG plus Markdown summary.

Then put limits around the next run:

npx -y martin-loop@0.9.0 enable --engine codex

npx -y martin-loop@0.9.0 run " " --verify "npm test" --budget-usd 2 --max-iterations 3

2-Minute Install Path

If MartinLoop detects more than one supported coding-agent runtime, save the one you want to use before the first governed run. For example:

npx -y martin-loop@latest enable --engine codex

Replace codex with claude or gemini when that is your intended runtime.

npx -y martin-loop@latest start

npx -y martin-loop@latest demo cd martin-loop-demo npm install npx -y martin-loop@latest run "Summarize the demo workspace and prove tests still pass" --verify "npm test" --budget-usd 2 --max-iterations 1

Quick Start

Try MartinLoop in a disposable demo workspace:

npx -y martin-loop@latest enable --engine codex

npx -y martin-loop@latest start npx -y martin-loop@latest demo npx -y martin-loop@latest --version cd martin-loop-demo npm install npx -y martin-loop@latest run "Summarize the demo workspace and prove tests still pass" --verify "npm test" --budget-usd 2 --max-iterations 1 npx -y martin-loop@latest dossier --latest npx -y martin-loop@latest share --latest

Optional global install:

npm install -g martin-loop

martin-loop --version

If this flow is useful, open an issue with feedback so we can keep improving the public experience.

start prints the first-run guided path. run auto-checks doctor, session-start, and preflight, then executes when the environment is ready. Use --proof only when you intentionally want an explicit no-spend lane.

Inspect-first flow:

npx -y martin-loop@latest enable --engine codex

npx -y martin-loop@latest doctor npx -y martin-loop@latest session-start npx -y martin-loop@latest preflight "Summarize the demo workspace and prove tests still pass" --verify "npm test"

share --latest writes three files into the selected run directory under share/: run-receipt.json, run-receipt.md, and proof-card.svg.

Release notes for MartinLoop 0.6.5: MartinLoop 0.6.5.

Release notes for MartinLoop 0.6.6: MartinLoop 0.6.6.

Release notes for MartinLoop 0.6.7: MartinLoop 0.6.7.

Release notes for MartinLoop 0.6.8: MartinLoop 0.6.8.

Release notes for MartinLoop 0.7.0: MartinLoop 0.7.0.

Release notes for MartinLoop 0.7.1: MartinLoop 0.7.1.

Release notes for MartinLoop 0.8.0: MartinLoop 0.8.0.

Release notes for MartinLoop 0.8.1: MartinLoop 0.8.1.

Release notes for MartinLoop 0.8.2: MartinLoop 0.8.2.

Release notes for MartinLoop 0.8.3: MartinLoop 0.8.3.

Release notes for MartinLoop 0.8.4: MartinLoop 0.8.4.

Release notes for MartinLoop 0.8.5: MartinLoop 0.8.5.

Release notes for MartinLoop 0.8.6: MartinLoop 0.8.6.

Release notes for MartinLoop 0.8.7: MartinLoop 0.8.7.

Release notes for MartinLoop 0.8.8: MartinLoop 0.8.8.

Release notes for MartinLoop 0.8.9: MartinLoop 0.8.9.

Release notes for MartinLoop 0.9.0: MartinLoop 0.9.0.

Swarm Mode Demo

Run the deterministic 15-agent launch-board demo without provider calls or spend:

npx -y martin-loop@0.9.0 demo --swarm

That default result is local simulation evidence only: it is non-governed, is not persisted to the Swarm run store, and does not evaluate signed receipt integrity. Inspect simulation output through the `demo

Only the beginning is shown; read the rest in the repo

Martin Loop

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

FOGA node

README from the maker

MartinLoop

Start Here

For AI Agents

One System Around the Run

Change the worker. Keep the job.

Why MartinLoop

Why Teams Adopt MartinLoop

See Your Loop Tax

2-Minute Install Path

Quick Start

Swarm Mode Demo