#qa
17 results found
Q-Anon Posts/Drops MCP Server
Model Context Protocol server for sociological research into QAnon
QA MCP (Probably will rename to vibecheck?)
[MCP Server] Complete QA for cursor -> (soon to be renamed to VibeCheck)
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.
GroundNG: QA for Cursor
Put cursor in a feedback loop - QA for cursor
VibeShift Web tester
[MCP Server] Complete QA for cursor
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.
VibeCheck Web tester
[MCP Server] Complete QA for cursor
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.
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.