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17 results found

Q

Q-Anon Posts/Drops MCP Server

Model Context Protocol server for sociological research into QAnon

Q

QA MCP (Probably will rename to vibecheck?)

[MCP Server] Complete QA for cursor -> (soon to be renamed to VibeCheck)

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QA Sphere MCP

A Model Context Protocol server for the QA Sphere test management system. This integration enables Large Language Models (LLMs) to interact directly with QA Sphere test cases, allowing you to discover, summarize, and chat about test cases. In AI-powered IDEs that support MCP, you can reference specific QA Sphere test cases within your development workflow.

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GroundNG: QA for Cursor

Put cursor in a feedback loop - QA for cursor

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VibeShift Web tester

[MCP Server] Complete QA for cursor

Q

QA Sphere MCP Server

MCP Server for QA Sphere TMS

🚀 operative.sh web-eval-agent MCP Server

An MCP server that autonomously evaluates web applications.

V

VibeCheck Web tester

[MCP Server] Complete QA for cursor

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Webvizio MCP

Webvizio MCP Server - Automatically converts feedback and bug reports from websites and web apps into actionable, context-enriched developer tasks. Delivered straight to your AI coding tools, the Webvizio MCP Server ensures your AI agent has all the data it needs to solve tasks with speed and accuracy.

Z

Zenable

Zenable cleans up sloppy AI code, prevents vulnerabilities, and automates governance with deterministic guardrails so developers can ship faster, safer, and with confidence. Use Cases: 1. AI coding assistants generate vulnerable code with security flaws and compliance violations. Zenable acts as a real-time safety net that catches SQL injections, hardcoded secrets, and policy violations as code is written - ensuring you ship AI-accelerated code with confidence and zero security compromises. 2. Rapid AI-driven development introduces inconsistent patterns and technical debt. Zenable provides automated governance checks that ensure every AI-generated feature meets your standards, enabling 10x development speed without sacrificing code quality. 3. Bugs slip through reviews and automated testing misses edge cases. Zenable provides AI-powered analysis that identifies subtle bugs and suggests fixes before production, resulting in fewer production incidents.

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