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mcp-benchmark-hygiene

mcp-benchmark-hygiene

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github.com/sudo-ai-gitDeveloper Tools0Updated 9w ago

About mcp-benchmark-hygiene

mcp-benchmark-hygiene is a deterministic MCP server that detects inherited pytest settings that can distort agent-benchmark grading. It checks workspace configuration and returns a corrected test command when grading gates are found.

Key features

  1. 01Trace pytest configuration to filesystem root
  2. 02Detect coverage and abort gates in addopts
  3. 03Classify workspaces as CLEAN, CORRUPTED, or UNKNOWN
  4. 04Return a corrected pytest command
  5. 05Provide concise analysis summaries

Use cases

  1. 01Diagnose benchmark results that fail despite passing code
  2. 02Check pytest settings inherited by nested workspaces
  3. 03Choose a test command that avoids host grading gates

MCP support

It exposes workspace inspection, addopts checking, and analysis summary tools to MCP clients over stdio or Streamable HTTP.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"sudo-ai-git-mcp-benchmark-hygiene": {
"command": "uvx",
"args": [
"mcp-benchmark-hygiene"
]
}
}
}
Run commanduvx mcp-benchmark-hygiene

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypimcp-benchmark-hygiene1.0.1

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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.:

[tool.pytest.ini_options]
addopts = "--cov=harness --cov-report=term-missing:skip-covered --cov-fail-under=80"

...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:

python -m pytest -o addopts= <tests>

-o addopts= strips inherited coverage/abort gates. (Or run the grader from outside the repo root.)

Tools

toolpurpose
inspect_workspace(path)full analysis: ini chain, effective addopts, CLEAN/CORRUPTED/UNKNOWN verdict + corrected command
check_addopts(path)thin boolean: corrupted + reasons
summarize(analysis)one-line actionable summary string

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:

uv tool install git+https://github.com/sudo-ai-git/mcp-benchmark-hygiene
mcp-benchmark-hygiene                        # run stdio server
mcp-benchmark-hygiene --http --port 8137     # or Streamable HTTP

Or with pipx: pipx install git+https://github.com/sudo-ai-git/mcp-benchmark-hygiene

Direct from source (fallback):

{ "mcpServers": {
    "benchmark-hygiene": { "command": "python3", "args": ["/abs/path/to/mcp_server.py"] }
}}

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)
python3 mcp_server.py --http --port 8137   # serves on http://<host>:8137/mcp/

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

inspect_workspace(path="/home/runner/vulcanbench/workspace/task-1")
→ {
    "ok": true,
    "workspace": "/home/runner/vulcanbench/workspace/task-1",
    "ini_chain": [{"file": "/home/runner/vulcanbench/pyproject.toml",
                   "addopts": "--cov=harness ... --cov-fail-under=80"}],
    "effective_addopts": "--cov=harness ... --cov-fail-under=80",
    "will_corrupt_grading": true,
    "verdict": "CORRUPTED",
    "fixed_command": ["python3", "-m", "pytest", "-o", "addopts=", "<tests>"],
    "reasons": ["coverage gate(s) present: ['--cov', '--cov-fail-under']"]
}

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:

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.

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