"QA review sentinel test marker" matching MCP servers:

Keyless, local MCP server bringing ISTQB / OWASP / IEEE / ISO / EU AI Act QA standards into your AI client. Standards-grounded retrieval, deterministic QA effort estimation, automated QA document quality review (0-100 rubric), and JUnit/CSV test-results flakiness analysis.

Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.

An MCP server that brings senior-QA discipline to AI coding assistants, enabling test planning, TDD, mutation testing, and code review.

Agent-Level Transaction Safety Oracle. Before an AI agent signs a blockchain transaction, it returns a SAFE/UNSAFE verdict with a SENTINEL Score (AAA-D) and risk flags. Pay-per-call $0.005 USDC via x402 on Base.

Enables Claude Desktop and Claude Code users to get AI-powered legal risk classifications for small business decisions, returning structured GREEN/YELLOW/RED verdicts with statute citations and compliant alternatives.

A local MCP server that routes QA reviews through deterministic profiles and risk-based escalation while keeping source evidence and final decisions with the host.

A code review tool that generates detailed HTML review documents by comparing branches or commits, with author filtering and intelligent analysis.

MCP server providing three QA tools: parse JUnit XML reports, detect flaky tests across multiple runs, and evaluate quality gates with pass/fail decisions.

Exposes surface-bound annotations placed on a Blender model to AI agents, letting them read pending change requests with stable IDs, revisions, positions and visibility, then submit completion summaries by marker ID after editing. This enables batch, review-oriented workflows where the user approves or rejects each agent change in Blender, without requiring object selection, screenshots, or a fixed port bridge.

An MCP server that runs curated adversarial prompts against local Ollama models to test guardrails, scoring responses with heuristic verdicts for human review.

An MCP server that reads test reports and provides regression analysis tools for comparing runs, identifying regressions, fixes, and persistent failures.

Evaluates MCP servers by running read-only checks and returning a graded report with an A-F letter grade.

An MCP server that scans code for exposed secrets (API keys, tokens, private keys, high-entropy strings) with placeholder-aware allowlisting and fully redacted reports, enabling agents to detect leaks before committing.

MCP server exposing IAMF conformance validation and packaging tools, enabling agents to validate IAMF files and compile/manage packaging plans through natural language, with read-only operation by default and optional execution.

MCP server that ranks and deduplicates your GitHub pull request review queue across direct requests, team requests, and your own waiting PRs into a single prioritized list via one get_review_queue tool.

A multi-agent literature review pipeline that uses specialized agents to research, peer-review, and synthesize academic and practitioner perspectives into grounded reports.

Enables LLMs to ingest and analyze legal agreements, compute risk scores, and monitor non-compliant clauses through MCP tools like ingest, fetch_contracts, and run_analysis.

A TypeScript-based MCP server that enables testing of REST APIs through Cline. This tool allows you to test and interact with any REST API endpoints directly from your development environment.

Provides bounded, read-only analysis of local project directories, enabling inventory, marker detection, and safe file reads without executing code.

Unifies prediction markets, global news events, aviation state, and internet-infrastructure telemetry into a single async MCP server for macro and financial analysis.