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"Converting Figma Files to React Code" matching MCP servers:

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    Fast, quota-free Figma automation for coding agents, enabling AI agents to read, edit, migrate, audit, screenshot, and prototype inside Figma Desktop files.
    4
    MIT
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    Figma MCP server with full read/write access via plugin bridge — no API token, no rate limits. 58 tools for design automation: styles, variables, components, prototypes, and content.
    73
    1,267
    MIT
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    Figma MCP server with full read/write access via plugin bridge — no API token, no rate limits. 83 tools for design automation: styles, variables, components, prototypes, and content.
    6
    MIT
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    Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.
    206
    MIT
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    AI modifies a function but misses 5 callers that also need updating. crag fixes this — it builds precise call graphs via static analysis, so AI knows exactly what's affected before making changes.
    2
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    RegressGuard is an MCP server that records a known-good baseline and lets AI coding agents detect regressions (broken API contracts, failing tests, schema changes) during their edit loop, allowing them to self-correct before committing.
    1
    MIT
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    An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.
    MIT
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    Your coding agent can read the code. It can't read the argument behind it. lema-mcp gives your agent the recorded why — and the alternatives a project already ruled out — cited to the source. For React, Kubernetes, and Rust out of the box, and for your own repo with one command.
    1
    MIT
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    Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.
    MIT
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    An MCP server for semantic code search & navigation that helps AI agents work efficiently without burning through costly tokens. Instead of reading entire files, agents can search conceptually and jump directly to the specific functions, classes, and code chunks they need.
    119
    MIT
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    MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.
    27
    AGPL 3.0
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    Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.
    16
    MIT
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    Converts URL content to Markdown, providing two tools: one for extracting main article content and one for converting the entire HTML.
    9
    MIT
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    Gives AI assistants direct access to macOS clipboard - letting Claude copy generated code, text, or files straight to your clipboard for pasting anywhere on Mac.
    244
    MIT