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"Tools to Enhance Cursor AI Performance" matching MCP servers:

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    Enables web performance analysis using Google PageSpeed Insights and Chrome UX Report APIs, providing compact metrics and diagnostics without local browser automation.
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    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
    3
    27
    Apache 2.0
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    Enables MCP clients like Claude Code and Codex to delegate coding tasks to Cursor's CLI agent, which implements changes in the workspace and returns clean, structured results for review.
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    MIT
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    MCP server for browsing, searching, exporting, and backing up your Cursor AI chat history directly into Claude via natural language.
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    MIT
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    An MCP server integration that enables Cursor AI to communicate with Figma, allowing users to read designs and modify them programmatically through natural language commands.
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    MIT
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    Enables interactive feedback with image support in Cursor, allowing users to paste images for visual context and feedback.
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    MIT
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    Enables Cursor AI to interact with Figma designs, allowing users to read design information and programmatically modify elements through natural language commands.
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    An interactive feedback MCP server that enables one conversation with unlimited AI interactions, bridging agent tools with Feishu for mobile replies.
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    MIT
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    A local MCP server that improves token efficiency for Cursor's agent by providing cheaper tools like search_code, outline_file, read_snippet, project_map, and handoff, along with rules that steer the agent to use them and reduce excessive context usage.
    MIT
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    Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.
    4
    Apache 2.0