"How to Convert Figma Designs to Code" matching MCP servers:

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

Enables mapping Figma designs to a project's own component library — shadcn/ui, antd, mui, or Astryx — by resolving variants against authoritative component contracts instead of guessing. It compiles Figma nodes into code and then deterministically writes the resulting files into the codebase, cleaning node-id artifacts and updating exports.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Enables AI coding assistants to semantically search codebases by meaning rather than exact text, with zero external daemons and fully local embeddings. Works out-of-the-box with Claude Code, Gemini CLI, Antigravity, and Cursor.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

AI-powered continuous code assistant for Cursor, VS Code, Antigravity, and Claude Code via MCP, providing tools for code review, testing, documentation, and quality analysis.

Connects Kimi Code with Claude Code, enabling Claude to delegate bulk codebase reading to Kimi (256K context) for cost savings, while Claude focuses on reasoning and code edits.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

Strict AI code reviewer powered by Groq. Finds bugs, vulnerabilities and security issues in your code. Supports analyze, compare versions, explain code, generate tests, and HTML reports.

Enables AI assistants to search, analyze, and understand multi-language codebases by providing indexed code intelligence via MCP.

A self-hosted semantic code retrieval MCP server that enables natural language queries to find relevant code snippets using Tree-sitter AST parsing, embedding, and hybrid search with reranking.