Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Deliberately faulty MCP server for testing how agent clients handle tool errors and disconnects.
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。
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。
选择你使用的 AI 应用,然后复制设置。
LAB_SCENARIO, LAB_DELAY_MS, LAB_FAILURES你需要
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"failure-lab": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"LAB_SCENARIO",
"-e",
"LAB_DELAY_MS",
"-e",
"LAB_FAILURES",
"ghcr.io/cloudlabworks/mcp-failure-lab:0.1.2"
],
"env": {
"LAB_SCENARIO": "your-value",
"LAB_DELAY_MS": "your-value",
"LAB_FAILURES": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add failure-lab --env LAB_SCENARIO=your-value --env LAB_DELAY_MS=your-value --env LAB_FAILURES=your-value -- docker run -i --rm -e LAB_SCENARIO -e LAB_DELAY_MS -e LAB_FAILURES ghcr.io/cloudlabworks/mcp-failure-lab:0.1.2运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"failure-lab": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"LAB_SCENARIO",
"-e",
"LAB_DELAY_MS",
"-e",
"LAB_FAILURES",
"ghcr.io/cloudlabworks/mcp-failure-lab:0.1.2"
],
"env": {
"LAB_SCENARIO": "your-value",
"LAB_DELAY_MS": "your-value",
"LAB_FAILURES": "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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"failure-lab": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"LAB_SCENARIO",
"-e",
"LAB_DELAY_MS",
"-e",
"LAB_FAILURES",
"ghcr.io/cloudlabworks/mcp-failure-lab:0.1.2"
],
"env": {
"LAB_SCENARIO": "your-value",
"LAB_DELAY_MS": "your-value",
"LAB_FAILURES": "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。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
LAB_SCENARIO envLAB_DELAY_MS envLAB_FAILURES env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。
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7日
注册名称已通过 GitHub 账户 cloudlabworks 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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
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。
它在 1 项适用的基础检查中通过了 1 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。
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)。
GitHub 仓库最后更新于–,最新版本(0.1.2)于4天前进入注册中心。
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 Docker。
同一分类中有:Spec Driven Development, Remote Desktop Commander, SuperCollider
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ 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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Make sound with SuperCollider: synths, drums, chords, melodies and soundscapes over OSC.
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。
A deliberately faulty MCP server and a bounded reference-client harness. v0.1.0, MIT. Built on the official MCP TypeScript SDK 2.3.1, not a replacement protocol implementation.
Requires Docker. The image uses Node 24 and pinned npm dependencies.
docker build -t mcp-failure-lab:local .
docker run --rm --network none --read-only --cap-drop ALL --security-opt no-new-privileges mcp-failure-lab:local npm test docker run --rm --network none --read-only --cap-drop ALL --security-opt no-new-privileges mcp-failure-lab:local node runner.mjs
The last command prints JSON results and OpenAI-message-shaped traces from seven deterministic runs. No language model participates. Timings are observed elapsed milliseconds, not benchmarks. The test command exits nonzero on a regression; the demo command emits observations, not a grading verdict.
For local development: npm ci --ignore-scripts, then npm test.
From the published image (Official MCP Registry: io.github.cloudlabworks/mcp-failure-lab):
docker run -i --rm -e LAB_SCENARIO=tool-error ghcr.io/cloudlabworks/mcp-failure-lab:0.1.2
From v0.1.2, each release has build provenance signed through Sigstore by the publish-mcp workflow. With the GitHub CLI:
gh attestation verify oci://ghcr.io/cloudlabworks/mcp-failure-lab:0.1.2 --repo cloudlabworks/mcp-failure-lab
gh attestation verify mcp-failure-lab-0.1.2.tar.gz --repo cloudlabworks/mcp-failure-lab
The second command checks the source tarball from the GitHub Release. To verify offline, add --bundle mcp-failure-lab-0.1.2.tar.gz.intoto.jsonl (the provenance file attached to the same release).
| LAB_SCENARIO | Injected behavior | Reference-client expectation |
|---|---|---|
| healthy | Normal tool response | One success |
| tool-error | Valid result with isError=true | Stop at configured attempt budget |
| transient-error | First LAB_FAILURES calls fail | Recover if the attempt budget permits |
| delay | Wait LAB_DELAY_MS before tool response | Succeed within deadline or time out |
| malformed | Valid JSON-RPC envelope, invalid text-block value | Reject the tool result |
| disconnect | Exit during a tool response | Report closed connection, not success |
Only the advertised lab_probe tool is affected. Initialization and discovery use the official SDK. The transport wrapper corrupts result shape, not JSON framing; truncated frames, bad IDs, HTTP failures and authentication faults are not implemented.
Configuration is read at process startup. Scenarios reset per process. LAB_DELAY_MS: integer 0–10000 (default 1000). LAB_FAILURES: integer 0–10 (default 2). Values must be plain decimal digits; an unset or empty variable uses the default, and anything else (0x10, 1e3, 7) stops the server with exit code 2. The reference client retries only explicit tool errors, at most five attempts; protocol errors, timeouts and disconnects stop immediately. The harness's tool-call deadline is 10–10000 ms; SDK connection/discovery deadlines are separate. Retries intentionally have no backoff so the generated fixture exposes repeated calls; this is not recommended production retry policy.
Configure a test MCP connection to run this command, with stdin/stdout attached:
docker run --rm -i --network none --read-only --cap-drop ALL --security-opt no-new-privileges -e LAB_SCENARIO=transient-error -e LAB_FAILURES=2 mcp-failure-lab:local
Call lab_probe with {"message":"probe"}. There are no real downstream services, credentials, file-writing tools or listening network ports. Client integrations beyond the included reference client are unverified.
From this repository, with Clinic checked out next to it:
mkdir -p artifacts
docker run --rm --network none --read-only mcp-failure-lab:local node runner.mjs > artifacts/run.json node --input-type=module -e 'import fs from "node:fs"; const r=JSON.parse(fs.readFileSync("artifacts/run.json","utf8")); console.log(JSON.stringify(r.results.find(x=>x.scenario==="tool-error").trace));' > artifacts/tool-error.json node ../agent-trace-clinic/cli.mjs artifacts/tool-error.json --html > artifacts/clinic-report.html
Clinic should identify tool_loop, retry_storm and unhandled_tool_error on this fixture. These are heuristic leads: deliberate bounded retries can also trigger them. No token counts are invented.
MCP conformance is the upstream authority for protocol tests. This project contributes a small fault surface for recovery experiments; it does not claim conformance certification. The official framework currently documents HTTP-based client/server scenario runners. This first release is stdio-only; an upstream scenario adapter and a Streamable HTTP target are next, not shipped capabilities.
Sources checked 2026-10-14:
One transport, one tool, six fault modes, one reference client. Pin SDK upgrades and rerun every fault test. Owner: Cloud Lab Works / Waku. Gherkin review has not been assigned or completed. Before public release: source/dependency review, an independent test pass, and publication approval. Before cloud execution: bounded job budget, teardown, and measured runtime. No cloud account is required for this release. No telemetry or remote reporting. Generated reports stay in ignored artifacts/.
Open the public demo or read the experiment guide. Four controlled before/after cases connect the official MCP reference client to deterministic Clinic inspection. The public sample is recorded local evidence, not a live cloud execution. Cloud adapters and runbook are included.
If you use this project, please cite the accompanying preprint: MCP Failure Lab: Reproducible Tool-Failure Fixtures and Cross-Platform Traces for Testing Agent Reliability. DOI: 10.5281/zenodo.23720942. See the paper page for the abstract and PDF.
@techreport{alvord2026mcp,
author = {Alvord, Alex}, title = {{MCP Failure Lab: Reproducible Tool-Failure Fixtures and Cross-Platform Traces for Testing Agent Reliability}}, institution = {CloudLab Works}, publisher = {Zenodo}, year = {2026}, month = oct, type = {Preprint}, doi = {10.5281/zenodo.23720942}, url = {https://doi.org/10.5281/zenodo.23720942} }