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    Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.
    9
    67
    1
    Apache 2.0
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    A local-first MCP server that scores your codebase's Build Readiness by reading code and running tests on your machine, outputting a diligence-grade score and risk register without uploading your source.
    5
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    Apache 2.0
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    A stdio MCP server that audits other MCP servers over the live protocol. It connects to any MCP target (stdio or HTTP), lints every tool's schema for agent-usability, then actually calls the tools with deliberately broken inputs to see how the server handles them, and returns a 0–100 conformance score with a per-dimension breakdown rendered as Markdown.
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    MIT
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    Enables AI assistants to interact with TrafficMorph for load-testing and CI-failure triage, including run management, profile lifecycle, and domain verification through natural language.
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    Apache 2.0
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    Gives AI agents a compact, semantic interface to the browser, returning structured page snapshots with stable element IDs instead of raw DOM. Enables agents to navigate, interact, and extract information from web pages efficiently.
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    MIT
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    Enables AI agents to formally verify constant-time, masking, and patch completeness properties of Verilog hardware designs, providing concrete leakage signals and next-step guidance.
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    Apache 2.0
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    This is an unofficial, community-built MCP server for qTest Manager. Not affiliated with or endorsed by Tricentis. Browse projects, modules, and test cases Create/delete test design modules Create and manage test execution cycles Add test cases into execution suites
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    MIT
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    Enables an agent to drive a real Ragnarok Online client session against a local rAthena server, allowing it to log in, walk, talk to NPCs, and fight in order to test server content end to end.
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    AI-native Model Context Protocol (MCP) server for TestRail. Lets Claude, Cursor, Windsurf, and other AI assistants browse projects, create and update test cases, kick off test runs, and record results through natural-language conversation — with strongly-typed tool schemas and per-project custom field validation that helps LLMs generate valid TestRail requests on the first try.
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    Apache 2.0
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    Enables AI-driven browser automation with advanced form testing, batch operations, and intelligent element extraction for MCP-compatible applications.
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    MIT
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    Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.
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    MIT