"The official Python standard library documentation" matching MCP connectors:
Matching Connector Tools:
Author and validate Calaf workspace seeds against the app's real importer. No account needed.
Verify scraped data against the live source page. Signed verdicts, $0.01 via x402.
Seven tools over the tabnas parsing engine: parse, validate, diagnose, fixtures, compare.
Point Claude Code, Qwen Code, Cursor, or any MCP client at https://docs.jmeter.ai/api/mcp and your agent answers JMeter questions grounded in this documentation, with a source link for every answer. Free, no API key, no signup.
Security + bug + perf + refactor audit for Python. Returns 0-10 score + MD report.
Grade MCP servers A to F with the open behavioral litmus. npm: full toolset; hosted: lookups only.
Check if your MCP server is ready to publish on the MCP Registry, Smithery, or npm.
Runs your code against a contract; returns HELD or BROKE at the exact input. Deterministic.
Read-only MCP server for the OPERANT AI operating-agent calibration benchmark.
Test the voice agents you run: scored transcripts, pass/fail verdicts, latency and WER metrics.
MCP server for the Fail Modes taxonomy — a knowledge base of AI system failure modes
PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc.
The world's first named AI prompt quality score. Score, optimize, and compare LLM prompts before they hit any model. Free tier available. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. x402-native on Base.
MCP server providing access to the Scorecard API to evaluate and optimize LLM systems.
You are the model under test. Enter ScoreIA Open Chamber; signed cards include failures. Auth none.
Official MCP server for Qase — manage test cases, runs, suites, defects via AI tools.
Estimated game fps for any GPU or Apple Silicon chip, with the limiter and tweaks.
SeaOtter dispatches work to a Superteam and checks the delivered outcome before money moves.
MCP Spec Compliance MCP — audits any MCP server.json against the official Model Context Protocol
Check AI work against requirements and return structured verdicts, findings, and repair steps.