{"name":"io.github.gvasile29/qai-consultant-mcp","slug":"gvasile29-qai-consultant-mcp","title":null,"description":"Keyless local MCP server for QA: standards retrieval, effort estimation, doc review, test analysis.","url":"https://mcp.market/server/gvasile29-qai-consultant-mcp","rating":null,"grade":"A","score":92,"certified":false,"status":"active","category":"other","tags":[],"presence":{"score":22,"stars":4,"forks":1,"downloads_week":null,"last_push_at":"2026-09-18T12:31:53.000Z","license":"NOASSERTION"},"uptime":null,"claimed":false,"transport":"pypi","callable_via_gateway":false,"default_price_micros":0,"repository":"https://github.com/gvasile29/qai-consultant","website":null,"version":"3.5.2","remotes":[],"packages":[{"registryType":"pypi","identifier":"qai-consultant-mcp","version":"3.5.2","transport":{"type":"stdio"}}],"tools":[{"name":"analyze_test_results","description":"Deterministic test-results health metrics (flaky / ever-failing / never-run / slowest / failure clustering) from real test execution data — no LLM anywhere in this call path; write your own narrative from the returned numbers. Provide exactly one of junit_xml or csv_text. junit_xml is normally one JUnit XML report string for one run (accepts both a <testsuites> and a bare <testsuite> root); to ana","write_action":false,"price_micros":0,"input_schema":null},{"name":"assess_qa_maturity","description":"Deterministically assess QA process maturity from a free-text project/ process description (or a pasted existing Test Strategy/Risk Register) — no LLM anywhere in this call path; write your own narrative from the returned findings. Scores 10 TMMi process areas (Level 2 Managed + Level 3 Defined) and returns an indicative_tmmi_level (1-3 — NEVER higher; Levels 4-5 require quantitative evidence a te","write_action":false,"price_micros":0,"input_schema":null},{"name":"estimate_qa_effort","description":"Deterministic QA effort estimate (PERT + complexity multipliers + team capacity + confidence score) — no LLM narrative; write your own from these numbers. Fields mirror the app's project-intake dialogue and are validated with the same rules; a validation failure returns {\"error\": \"validation\", \"fields\": {field: message}}, never a crash. Success returns the full EstimationData as JSON (baseline, mu","write_action":false,"price_micros":0,"input_schema":null},{"name":"list_kb_sources","description":"List every document in the knowledge base, grouped by category. Returns {\"categories\": {category: [{\"source\", \"title\"}]}, \"kb_version\", \"doc_count\"}.","write_action":false,"price_micros":0,"input_schema":null},{"name":"retrieve_qa_knowledge","description":"Retrieve grounding chunks from the QA knowledge base (ISTQB, OWASP, IEEE, ISO standards; testing methodologies; audit/evaluation frameworks; the EU AI Act). Returns {\"chunks\": [{\"source\", \"category\", \"text\", \"score\"}], \"kb_version\"}. category, if given, must be one of: Standard, Methodology, Article, Expert Knowledge, Audit/Evaluation — an unrecognized value returns a structured {\"error\": \"invalid","write_action":false,"price_micros":0,"input_schema":null},{"name":"review_qa_document","description":"Deterministically review an existing QA document (Test Plan, Test Strategy, or a test case list) against a six-dimension ISTQB/IEEE-829- grounded rubric (structure completeness, objectives & scope clarity, entry/exit criteria, traceability, measurability, risk coverage) — no LLM anywhere in this call path; write your own narrative from the returned findings. doc_type must be one of \"auto\", \"test_p","write_action":false,"price_micros":0,"input_schema":null}],"scan":{"score":92,"grade":"A","scanned_at":"2026-09-19T19:49:43.492Z","report":{"scannerVersion":"0.1.5","scannedAt":"2026-09-19T19:49:43.470Z","components":{"code":{"score":25,"max":25,"notes":["13 source files scanned"]},"reliability":{"score":-1,"max":20,"notes":["no gateway calls yet and no remote to probe"]},"poisoning":{"score":-1,"max":15,"notes":["tools not inspected (local package is not executed); not counted"]},"auth":{"score":12,"max":15,"notes":["local package, no credentials required"]},"maintenance":{"score":15,"max":15,"notes":["last push 1 days ago"]},"identity":{"score":8,"max":10,"notes":["registry namespace matches repository owner","GitHub account older than a year"]}},"findings":[],"inputs":{"packages":[{"registryType":"pypi","identifier":"qai-consultant-mcp","version":"3.5.2","found":true,"license":"Apache-2.0","dependencyCount":99,"publishedAt":"2026-09-15T09:08:38.592172Z","repositoryUrl":"https://github.com/gvasile29/qai-consultant"}],"repo":{"found":true,"owner":"gvasile29","repo":"qai-consultant","archived":false,"pushedAt":"2026-09-18T12:31:53Z","stars":4,"forks":1,"openIssues":2,"ownerType":"User","ownerAvatarUrl":"https://avatars.githubusercontent.com/u/205189131?v=4","ownerCreatedAt":"2025-03-27T13:54:48Z","license":"NOASSERTION"},"icon":{"url":null,"source":"none"},"presence":{"stars":4,"forks":1,"downloadsWeek":null,"license":"NOASSERTION","lastPushAt":"2026-09-18T12:31:53.000Z","score":22}}}},"grade_history":[],"reviews":[]}