
Mcp Benchmark Hygiene
io.github.sudo-ai-git由 GitHub 账号 sudo-ai-git 发布v1.0.1更新于 Oct 24, 2026
Detect pytest config-leakage that corrupts agent-benchmark grading. Deterministic, no-LLM.
概览
一个本地运行的确定性 MCP 服务器,用于检查 pytest 工作区是否继承了宿主机的覆盖率或中止门禁,从而把通过的代码误判为失败。
- 可以做什么
- 检查工作区路径,沿 pytest 配置链(pyproject.toml、pytest.ini、tox.ini、setup.cfg)一直向上查找到文件系统根目录,得出实际生效的 addopts,并返回 CLEAN、CORRUPTED 或 UNKNOWN 结论,损坏时附带修正后的命令。执行轻量布尔检查,报告工作区是否损坏及原因。根据分析结果生成一行可执行的摘要。
- 适用场景
- 适用于运行或排查自动化智能体评测框架的场景:这些框架在嵌套于带有自身 pytest 配置的仓库下的目标工作区中调用 pytest,而你怀疑评分失败源于继承的覆盖率或中止门禁,而非代码本身。
- 运行要求
- 作为本地 stdio 进程运行,可用 uv 或 pipx 从项目 Git 仓库安装,或用 python3 直接从源码启动。服务器需要官方 mcp Python 包;检测核心本身无依赖。不需要网络访问、账户、密钥或环境变量。
安装
在 SourceWeft 中
- 打开 控制台中的 Mcp Benchmark Hygiene,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
mcp-benchmark-hygiene
mcp-name: io.github.sudo-ai-git/mcp-benchmark-hygiene
Deterministic detection of pytest config-leakage that silently corrupts agent-benchmark / function grading.
No LLM. No network. One question, answered reliably:
If I run
python -m pytest <tests>inside this workspace, will it inherit a host coverage/abort gate that mis-scores passing code as failed?
The bug this catches
Automated agent-evaluation harnesses often run python -m pytest <hidden_tests>
inside the target's workspace. If that workspace nests under a repo root carrying
pytest addopts — e.g.:
...pytest resolves that host pyproject.toml as its rootdir, inherits the
addopts, and fails on the host's own coverage gate (harness collected at
0% → below threshold → non-zero exit). The harness then records functionally
PASSING code as FAILED.
This is exactly the bug documented in
sudo-ai-git/vulcanbench-findings:
VulcanBench's declarative grader mis-scored every functional task as 0.0 for
this reason; with -o addopts= neutralizing the leak, the same workspaces passed
10/10.
The fix it hands you
When a workspace is flagged CORRUPTED, the tool returns the corrected command:
-o addopts= strips inherited coverage/abort gates. (Or run the grader from
outside the repo root.)
Tools
Deterministic core (no deps)
The analysis walks the workspace directory up to filesystem root, reading
pyproject.toml / pytest.ini / tox.ini / setup.cfg in pytest's
first-found order, and extracts addopts. Flags:
- coverage gates —
--cov,--cov-fail-under,--cov-report,--cov-config - abort/strict gates —
--maxfail,-x,--strict,--strict-markers,--pdb,--ff
Only gates that change exit codes / abort grading are flagged. A harmless
addopts is reported CLEAN with the exact string.
Install & run (MCP stdio)
One command (recommended) — installs from the repo, no PyPI token needed:
Or with pipx: pipx install git+https://github.com/sudo-ai-git/mcp-benchmark-hygiene
Direct from source (fallback):
Requires the official mcp python package (pip install mcp). The deterministic
core (inspect_workspace / check_addopts / summarize) imports and runs with
zero dependencies — the mcp package is only needed for the stdio server.
Streamable HTTP (remote/Smithery-publishable)
Run with --http to serve over Streamable HTTP (a remote MCP endpoint) instead of
stdio. This is the transport smithery mcp publish <url> expects for URL-based
publishing — so once a Smithery service token exists, the server deploys as-is.
Example
Verification
python3 test_detector.py— 5/5 core detection checks (root gate, nested inheritance, clean, abort gate, pyproject-no-pytest)python3 test_e2e.py— drives the real MCP stdio transport (initialize → tools/call) and asserts CORRUPTED / CLEAN thread through the wire
Part of a family
This is one of three deterministic, no-LLM agent-trust MCP servers by sudo-ai-git:
mcp-skill-sec— pre-install skill/security auditmcp-verify-claim— evidence-gated, honestly-tiered claim reportingmcp-benchmark-hygiene— pytest config-leakage / eval-honesty detection (this repo)
Sibling product: mcp-token-saver — token-cost proxy + analyzer for agent conversations (dedupes redundant tokens before they're billed; live-proven 74% cut). Discussion
Also in the family (a free CLI, not an MCP server): harness-audit — deterministic agent-eval / benchmark-grading hygiene audit that catches the same silent config-leakage mis-scoring class. Free lead-magnet; the same verification discipline, zero dependencies, auditable line-by-line.
License & provenance
MIT. Independently derived from the documented VulcanBench #79 finding; no endorsement by or affiliation with morganlinton/VulcanBench implied.
Hire a custom integration
Need this connected to your internal system (auth, logging, security-scan pass, hosted)? Open a custom-build request. MIT reference assets are free to use either way.
来源:README.md,提交 5931318
工具
0版本历史
1- v1.0.1最新Sep 16, 2026
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