原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

FetchSandbox

作者:fetchsandbox版本 0.7.30i★ –i电脑或云端
注册名称io.github.fetchsandbox/mcp

安装

概览

作者提供的说明(英文原文)

A deterministic verification engine for agents. Proves a fix: fails on the old code, passes on new.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 电脑或云端
  • 传输方式: stdio, Streamable HTTP
  • 分类: 开发者工具
  • 你需要填写:FETCHSANDBOX_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://fetchsandbox.com/mcp/v1

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "fetchsandbox": {
      "command": "npx",
      "args": [
        "-y",
        "fetchsandbox-mcp"
      ],
      "env": {
        "FETCHSANDBOX_API_KEY": "your-value",
        "FETCHSANDBOX_TELEMETRY": "your-value",
        "FETCHSANDBOX_BASE_URL": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http fetchsandbox https://fetchsandbox.com/mcp/v1

或者在你的电脑上运行

claude mcp add fetchsandbox --env FETCHSANDBOX_API_KEY=your-value --env FETCHSANDBOX_TELEMETRY=your-value --env FETCHSANDBOX_BASE_URL=your-value -- npx -y fetchsandbox-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "fetchsandbox": {
      "url": "https://fetchsandbox.com/mcp/v1"
    }
  }
}

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "fetchsandbox": {
      "command": "npx",
      "args": [
        "-y",
        "fetchsandbox-mcp"
      ],
      "env": {
        "FETCHSANDBOX_API_KEY": "your-value",
        "FETCHSANDBOX_TELEMETRY": "your-value",
        "FETCHSANDBOX_BASE_URL": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "fetchsandbox": {
      "type": "http",
      "url": "https://fetchsandbox.com/mcp/v1"
    }
  }
}

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "fetchsandbox": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "fetchsandbox-mcp"
      ],
      "env": {
        "FETCHSANDBOX_API_KEY": "your-value",
        "FETCHSANDBOX_TELEMETRY": "your-value",
        "FETCHSANDBOX_BASE_URL": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://fetchsandbox.com/mcp/v1

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • FETCHSANDBOX_API_KEY 机密 env
    Sign in using an account API key. Discovery is available anonymously; application planning, verification and managed local tunnels require authentication.
  • FETCHSANDBOX_TELEMETRY env
    Set to '0' to disable anonymous usage telemetry.
  • FETCHSANDBOX_BASE_URL env
    Override the FetchSandbox backend base URL (defaults to https://fetchsandbox.com). Useful for stage/self-hosted testing.

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。

它能做什么

工具名称和描述与服务器在 2026年11月7日 报告的完全一致。这些内容由作者撰写,不是我们写的;我们以纯文本形式显示。

  • coach

    Conversational integration coach for FetchSandbox. Server-side orchestrator that walks the user through adding an API integration (payments / email / auth / etc.) — intake the goal, elicit domain-aware discovery questions from the spec's brain.yaml, route to the right workflow, p

  • get_job

    Retrieve the SAME running find_bugs, fix_bug, prove_fix, verify_behavior or validate_integration job (including requirements planning). Follow next_tool_call until status is done or error. Never restart the original tool to poll. A proposed plan is not execution proof; a running

  • guide

    ROUTE a symptom to the provider behaviour that explains it. Use this when the user names a provider or a domain (payments, email, auth, SMS, subscriptions) and you need to know what that provider ACTUALLY does — not what its docs say, and not what can be inferred from reading the

  • quickrun

    Run a curated reference workflow against a KNOWN, bundled spec (stripe, clerk, descope, resend, twilio, and 50+ others) in ONE call — it spins up the sandbox by slug, so you do NOT need import_spec or a sandbox_id first. Use this when exploring the bundled provider contract: call

  • validate_integration

    Completion rule: a request to verify an app includes its applicable failure checks without another user prompt. When verification_continuation.required is true, continue in this agent: inspect pending_checks, preserve every declared check and its assertions, implement supported a

  • list_workflows

    List the named, runnable workflows for a known provider slug or imported spec. Workflows are realistic multi-step API journeys (e.g. 'create customer → attach payment method → create subscription'). Known provider slugs need no import. Use this for exploration ("what can I do?",

  • run_workflow

    Execute ONE specific workflow by name and return its step-by-step trace PLUS a `share_url` — a public, replayable proof URL that renders the full timeline (every request, response, webhook event) for this run. The share_url is the canonical 'here's what happened' artifact: surfac

  • verify_behavior

    Prove a known fix survives a bug — the 'prove' half of reproduce→prove. The backend spawns a buggy AND a fixed reference handler and fires the bug_pattern's probes at both, returning the side-by-side diff (e.g. the buggy handler double-charges on a duplicate webhook, the fixed ha

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8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 fetchsandbox 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • ✓ 通过

    端点有响应

    在 313 毫秒内响应(HTTP 200)

  • – 不适用

    使用 OAuth 登录

    无需登录

  • ✓ 通过

    工具描述中没有隐藏指令

    已读取 8 个工具描述,未发现针对 AI 的隐藏指令

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 4933 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 4933 个服务器的 66% 更新
  • 基础检查结果等于或优于此分类中其他 4933 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

FetchSandbox 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?

你需要填写:FETCHSANDBOX_API_KEY

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.7.30)于20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。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

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.

作者:github广泛使用★ 3.4万5天前更新

电脑或云端

Desktop Commander

MCP server for terminal commands, file operations, and process management

作者:wonderwhy-er广泛使用↓ 71万/周★ 1万17天前更新

在你的电脑上运行

Cloudflare MCP

Cloudflare MCP servers

作者:cloudflare正在增长★ 444614个月前更新

在云端运行✓ mcp.cloudflare.com

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。

fetchsandbox-mcp

Also on Smithery, npm and the official MCP registry.

A deterministic verification engine for agents, as an MCP server for FetchSandbox.

Your agent writes an integration. This checks whether it actually works — against a sandbox that behaves like the real provider, including the failures: retried webhooks, declined cards, rate limits, auth errors.

When it finds a bug, it can propose a fix and then prove it: the same failure is run against your code before and after the diff. Green only if it reproduced first and stopped after. You get a receipt URL either way.

Install

The MCP server runs locally through Node.js. Clients can resolve npx differently; Cursor on Mac may need the full path from command -v npx.

{

"mcpServers": { "fetchsandbox": { "command": "npx", "args": ["-y", "fetchsandbox-mcp@latest"], "env": { "FETCHSANDBOX_API_KEY": "fsk_your_key_here" } } } }

Discovery and reference tools are available without a key. Application planning, verification and managed local tunnelling require sign-in or an API key from https://fetchsandbox.com/keys. See Accounts.

ClientFile
Claude Code.mcp.json in your project root, or claude mcp add
Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.json
Cursor~/.cursor/mcp.json, or .cursor/mcp.json in the repo
Zed~/.config/zed/settings.json, under context_servers
Codex~/.codex/config.toml, as [mcp_servers.fetchsandbox]
Cursor on Mac: tested setup

Get a real account key from https://fetchsandbox.com/keys. Run command -v npx and use that full path in ~/.cursor/mcp.json. This example is for Homebrew on Apple Silicon; replace the path if yours differs. On Windows, use where.exe npx to locate your installed command.

{

"mcpServers": { "fetchsandbox": { "command": "/opt/homebrew/bin/npx", "args": ["-y", "fetchsandbox-mcp@0.7.24"], "env": { "FETCHSANDBOX_API_KEY": "fsk_your_key_here" } } } }

Replace fsk_your_key_here privately with the real raw key, without a Bearer prefix. The placeholder cannot authenticate. Check for a second FetchSandbox entry in .cursor/mcp.json in your project. Fully quit and reopen Cursor after saving; a window reload may retain the old MCP process. Enable the server if needed and confirm its tools load. A green connection alone does not prove that an application verification call is authenticated.

Restart the client afterwards. Anything else that speaks MCP takes the same command and args.

No terminal? Use the hosted endpoint

Browser-based builders — Lovable, Bolt, v0 — can't run npx. They connect straight to the hosted streamable-HTTP transport instead:

https://fetchsandbox.com/mcp/v1

Authenticate with a Bearer token, not "None" — paste the key from https://fetchsandbox.com/keys.

Same twins, same scenarios, seven tools: validate_integration, quickrun, run_workflow, verify_behavior, list_workflows, guide, coach.

The rest are not hidden — they cannot work there. find_bugs, fix_bug and prove_fix read your project from disk and a hosted server has no copy of it, so advertising them only produced sessions that dead-ended. To analyse your own code, run npx fetchsandbox-mcp locally in the project you want looked at.

Start with validate_integration. A green quickrun proves the provider behaves as documented; it does not touch your checkout endpoint, your webhook handler, or your email send. validate_integration hands you a fresh twin per provider and then reports what your code actually called.

Using it

Describe the problem the way you'd describe it to a colleague. You don't need to name a tool.

Customers are reporting more seats than they bought after a Paddle payment.

Can you find out why?

The agent works through: route the symptom, reproduce it against the provider sandbox, read your code, get a fix, prove the fix on your code. Each step hands back what the next one needs.

One thing worth knowing, because it's easy to get backwards: prove_fix needs the unfixed tree. Run it before you write the diff to disk, or there's no bug left to reproduce and no proof to be had.

Accounts

You don't need one to start. Install it, ask a question, and everything runs.

The first time a run produces something worth keeping — a receipt, or a set of findings — you'll get a short code and a link. Signing in takes about twenty seconds and does two things: the evidence behind your receipts stops being archived after 15 days, and the runs from that machine collect in one place. You'll be asked at most once a day, and never once you're signed in.

For CI, the hosted endpoint, or anywhere a browser isn't available, set a key instead. Create one at https://fetchsandbox.com/keys — sign in, then "Create a key". It looks like fsk_....

In an MCP client config, it goes in env:

"env": { "FETCHSANDBOX_API_KEY": "fsk_your_key_here" }

In a shell or CI:

export FETCHSANDBOX_API_KEY=fsk_your_key_here

On the hosted endpoint, send it as Authorization: Bearer fsk_....

The key is also written to ~/.fetchsandbox/credentials.json when you sign in from an editor; the environment variable always wins.

Tools

Start with guide. It picks the right ones for what you asked.

Finding and fixing

ToolWhat it doesArguments
guideRoutes a symptom to a spec, workflow and known failure classintent*, hints
find_bugsAudits your project against known integration failure classes. No git remote needed — it reads the directory you point it atpath, spec, timeout_s
fix_bugReturns a git diff for one finding. Doesn't touch your filesbug*, fix_pattern, path, spec, timeout_s
get_jobRetrieve the same running job without starting another analysis or proofjob_id*
prove_fixRuns the failure against your code before and after the diff. Green only on a measured flipdiff*, bug, scenario, sandbox_id, path, timeout_s

Verifying an integration

ToolWhat it doesArguments
validate_integrationProves your own code against a provider, not that our twin works. Hands back a fresh twin per provider, then reads our request log to report what your app actually calledproviders, app_base_url, session_id
quickrunRuns one of OUR curated workflows against a bundled spec. Green here says the provider behaves as documented — it says nothing about your integrationspec_slug*, workflow_name*, scenario
run_workflowThe same, on a sandbox you already have — this is where you re-run with a scenario armedsandbox_id*, workflow_name*, scenario
verify_behaviorShows a failure class on reference handlers — buggy vs fixed. Not your codebug_pattern_id*, prompt, sandbox_id, flow_run_id
list_workflowsWorkflows AND the failure scenarios a spec can inject, in one answerspec_slug or spec_id
guideRoutes a symptom to the provider behaviour that explains it, and returns the next call with its arguments filled inintent*, hints
coachMulti-turn help building an integrationintent, session_id, user_response, context

Those seven are the whole of what a browser-based builder sees, and they are the only ones that need no filesystem. Everything below requires a local project.

On a machine with your code

ToolWhat it doesArguments
find_bugsAudits your project against known integration failure classespath, spec, timeout_s
fix_bugReturns a git diff for one finding. Doesn't touch your filesbug*, fix_pattern, path, spec, timeout_s
get_jobRetrieve the same running job without starting another analysis or proofjob_id*
prove_fixRuns the failure against your code before and after the diff. Green only on a measured flipdiff*, bug, scenario, sandbox_id, path, timeout_s
run_all_workflowsRuns several workflows in one callsandbox_id*, workflow_names
list_scenariosThe failures a spec can injectsandbox_id*
set_scenarioArms a failure on a sandboxsandbox_id*, scenario*
list_runsPast runs for a sandboxsandbox_id*, limit
list_specsSpecs already availablefilter
submit_proofPublishes a receipt for a runsandbox_id, flow_run_id, bug_pattern_id, summary, proofs

* = required.

What leaves your machine

find_bugs, fix_bug and prove_fix package the directory you point them at and upload it for analysis. Worth saying plainly, because the previous wording here implied the opposite.

Excluded before packing: .git, node_modules and build output, agent instruction files, and anything credential-shaped — .env*, *.pem, *.key, id_rsa*, *.tfstate, .npmrc, .aws, .ssh, .mcp.json, .mcp.*.json, mcp.json, and more.

Then the archive is read back and refused if it still contains something shaped like a live credential, wherever it lives and whatever it is called. A key in config/local.yml stops the upload and names the file. Patterns only cover what someone thought of; the scan is there for the rest.

If you would rather nothing left at all, the analysis needs the source today. That is the honest state.

Long-running work

The MCP response waits briefly, then returns status: running, its job_id, and a next_tool_call for get_job. Follow that call until status: done or error. It reads the existing backend job; it does not upload the project again or start another proof. Keep the original tree unchanged while the proof runs. A running job does not establish a pass.

This applies to discovery, proposed fixes, application proofs, and async reference verification. Direct library calls keep their blocking behavior. Job retention and ownership still belong to the existing backend. This change does not make its in-memory job tracker survive a backend restart.

Receipts are public to anyone holding the link

submit_proof attaches the real requests and responses from your app's before/after run to the receipt page, so the receipt shows your code's own behaviour. That page is served without a login — that is the point of it, you drop the link in a PR — which means the bodies on it are readable by anyone who has the link.

Provider execution can use a FetchSandbox twin or a recording test double; read the receipt's execution scope. A recording double does not establish twin or live-provider fidelity. But the request bodies are the ones your app built, and those can carry values from your config. Look at a receipt before you share it.

Configuration

Env varDefaultPurpose
FETCHSANDBOX_API_KEYnoneSign in without a browser. Overrides the stored credentials
FETCHSANDBOX_BASE_URLhttps://fetchsandbox.comPoint at a different backend
FETCHSANDBOX_TELEMETRYonSet to 0 to turn off

Telemetry records an opaque per-machine id (a random UUID in ~/.fetchsandbox/session.json), the tool name, latency, and whether the call succeeded. Not

只显示了开头部分;其余内容请在仓库中阅读

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