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    A comprehensive MCP server for SEO, performance, GEO, and UX audits with 37 tools covering technical SEO, Lighthouse performance, AI search optimization, content analysis, accessibility, security, and more.
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    MIT
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    Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.
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    Apache 2.0
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    Enables AI-first accessibility testing by investigating pages, explaining findings, and applying fixes via natural language, integrated with Playwright tests and local or cloud AI models.
    MIT
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    Release gate agents call before they tell users a public website is ready to ship. Scans public websites across security, SEO, accessibility, legal compliance, and sustainability.
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    MIT
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    Accessibility-first LaTeX publishing engine with an embedded MCP server. Tools to list registered documents, render template-driven documents, and audit built PDFs for PDF/UA-2 / WTPDF / PDF/A-4f conformance with veraPDF. MIT-licensed.
    4
    MIT
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    AI-powered exploratory QA agent. Explores web apps like a real user — 18 MCP tools for clicking, filling forms, and navigating. Automatically verifies that actions persist (fake deletes, failed edits). Runs 16 detection types including dead links, SEO, accessibility, and performance checks.
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    MIT
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    Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.
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    MIT
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    Diffgate MCP server acts as a code review engine, enabling AI coding agents to analyze and validate code diffs before application. It enhances AI workflows by providing self-checking capabilities to optimise and secure code changes.
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    Apache 2.0
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    A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.
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    Apache 2.0
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    Connects AI coding assistants to TestCollab for managing test cases, plans, and suites directly through natural language. It enables users to create, update, and query testing resources within integrated development environments and AI chat clients.
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    MIT