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    Read-only MCP server that exposes the agentic-os governance, SDLC, and Quality Engineering methodology to any MCP host. It never writes to your repository and never executes code — it serves the methodology, plans an install, and verifies it, handing any commands back to the host to run.
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    Apache 2.0
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    An MCP server exposing every documented Email on Acid API v5 request as a tool — 24 tools across authentication, email client lists, email rendering testing, and spam testing.
    MIT
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    Enables browser automation through Playwright using accessibility tree snapshots instead of screenshots. Supports web scraping, form interactions, testing, and connecting to existing browser sessions with logged-in accounts.
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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.
    22
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    4
    Apache 2.0
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    Godot 4 MCP server with: Test running (GUT/GdUnit4) with structured pass/fail results API docs search with 30+ Godot 3→4 migration mappings Script analysis detecting 10 common GDScript pitfalls Scene/resource file parsing with antipattern detection Viewport screenshot capture LSP diagnostics from Godot's language server TypeScript, cross-platform (macOS/Windows/Linux), published on npm
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    8
    MIT
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    A unified MCP server for multi-stand infrastructure testing, enabling REST API calls, PostgreSQL queries, and OpenSearch searches through a single config file.
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    MIT
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    Enables AI-driven testing and automation of Tauri desktop applications through natural language, allowing users to interact with UI elements, capture screenshots, execute commands, and test application flows without manual clicking or complex scripts.
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    MIT
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    Enables comprehensive interaction with the BugBug test automation platform through its API. Supports running tests, monitoring execution status, managing test suites, retrieving results and screenshots, and performing batch operations through natural language commands.
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    Enables AI assistants to interact with TestRail test management systems through comprehensive API integration. Supports retrieving and updating test cases, projects, suites, runs, and results, plus adding attachments and managing test data through natural language commands.
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    MIT