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"Front-end MCP services related to Vue" matching MCP servers:

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    Enables real-time debugging and state manipulation of Vue.js applications through MCP protocol, integrating with Vue DevTools to access component trees, states, router info, and Pinia stores.
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    MIT
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    A thin MCP server that wraps provenance-receipts and quality-gate services as tools, enabling AI agents to certify content origin and score quality via Ed25519-signed receipts.
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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
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    A specialized testing harness that enables AI assistants to thoroughly test other MCP servers by connecting to them, discovering their tools/resources/prompts, executing test calls, and performing end-to-end validation with LLM integration.
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    MIT
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    Unity Editor adapter for the DCC MCP ecosystem, providing tools to inspect and modify Unity projects, scenes, builds, and diagnostics through a WebSocket bridge.
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    MIT
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    An experimental MCP v2 server supporting streamable HTTP, skills, and apps with a verification dashboard for end-to-end testing.
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    MCP server for the Ghost Inspector API that lets agents inspect and manage end-to-end browser tests, offering read-only tools for inventory, module usage, and stale test analysis, plus opt-in guarded write operations.
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    MIT
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    MCP server for autonomous end-to-end testing with Wopee.io. Analyzes web applications, generates and executes Playwright-based functional tests, and validates results — all driven by natural language commands.
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    MIT
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    Enables AI assistants to build, drive, and observe Android/KMM apps end-to-end through ADB and Gradle, with tools for UI automation, error capture, and testing.
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    MIT
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    mcp-test-runner is an MCP server that lets your AI client (Claude / Cursor / Codex / Gemini) drive your entire QA loop end-to-end: * Run tests across pytest / Jest / Cypress / Go / Maestro — single MCP surface, one env var to switch * Analyze a URL (Web DOM probe) or a live mobile screen (Maestro hierarchy) to extract testable modules + candidate cases * Generate runna
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    MIT