Martin Loop
What it does
One system around coding agents to run, verify, recover, and hand off software work.
- Connects 在你的电脑上运行
- Account or key No key needed
- Category 开发者工具
安装
选择你使用的 AI 应用,然后复制设置。
通过 3/3 项检查 · 在你的电脑上运行 · ✓ 命令已检查 2026年11月13日
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
需要先在电脑上安装 Node.js(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
打开电脑版 Claude 应用的设置文件
SettingsDeveloperEdit Config
粘贴这些设置并保存文件
{ "mcpServers": { "martin-loop": { "command": "npx", "args": [ "-y", "@martinloop/mcp" ] } } }退出 Claude 再重新打开
试一试
用 Martin Loop 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Martin Loop,或回答中出现 Martin Loop 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Martin Loop
Martin Loop 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
你可以改用这些方式
A · 使用能连接 Martin Loop 的应用
- 需要先在电脑上安装 Node.js(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
- 需要先在电脑上安装 Node.js(只需一次)
- 需要先在电脑上安装 Node.js(只需一次)
- 需要先在电脑上安装 Node.js(只需一次)
B · 开发者工具 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
- Sentry✓ ChatGPT
- Compiler Explorer✓ ChatGPT
- GitDiagram✓ ChatGPT
可连接 Claude Code,但需要先准备
需要先在电脑上安装 Node.js(只需一次)
打开终端
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
粘贴这条命令并按 Enter
claude mcp add --scope user martin-loop -- npx -y @martinloop/mcp在 Claude Code 中输入 /mcp
应能看到 Martin Loop 在列表中并显示已连接
试一试
用 Martin Loop 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Martin Loop,或回答中出现 Martin Loop 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor,但需要先准备
需要先在电脑上安装 Node.js(只需一次)
在 Cursor 中以 Agent 模式打开 AI 聊天
试一试
用 Martin Loop 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Martin Loop,或回答中出现 Martin Loop 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code,但需要先准备
需要先在电脑上安装 Node.js(只需一次)
在 VS Code 中以 Agent 模式打开 AI 聊天
试一试
用 Martin Loop 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Martin Loop,或回答中出现 Martin Loop 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
开发者专用:终端命令和 JSON 设置
安装在电脑上
Claude Code
claude mcp add --scope user martin-loop -- npx -y @martinloop/mcpClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"martin-loop": {
"command": "npx",
"args": [
"-y",
"@martinloop/mcp"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"martin-loop": {
"command": "npx",
"args": [
"-y",
"@martinloop/mcp"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"martin-loop": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@martinloop/mcp"
]
}
}
}这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
一览
哪些应用可以使用它
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它能做什么
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
基础检查i
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月14日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 Keesan12 验证,该账户拥有此仓库
- ✓ 通过
仍在维护
代码最后更新于10天前
- ✓ 通过
有许可证
使用 Apache-2.0
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行;我们只能读取互联网端点的工具列表
讨论
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
用户评价
还没有评价
与“开发者工具”中的其他服务器比较i
- 星标数多于此分类中其他 5880 个服务器的 98%
- 发布到注册中心的时间比此分类中其他 5880 个服务器的 69% 更新
- 基础检查结果等于或优于此分类中其他 5880 个服务器的 100%
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
常见问题
Martin Loop 安全吗?
它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
它需要哪些密钥或代码?
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在我的电脑上运行还是在云端?
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
它还在维护吗?
GitHub 仓库最后更新于10天前,最新版本(0.9.0)于10天前进入注册中心。
哪些应用可以使用它?
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
有什么可以替代它?
同一分类中有:REA, GitHub, Serena MCP: the IDE for your agent
同类别的其他选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Serena MCP: the IDE for your agent
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
作者的 README
打开 README
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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