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

Fast, quota-free Figma automation for coding agents, enabling AI agents to read, edit, migrate, audit, screenshot, and prototype inside Figma Desktop files.

Token-efficient Figma MCP server with image export, query DSL, and design token support.

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.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

MCP server that provides AI coding assistants with access to call graphs, data flows, and security analysis for multi-file vulnerability detection.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.

An MCP server for fast local source code searching using Zoekt, enabling regex and substring queries across indexed directories.

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.

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.

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.

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.

Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.

Connect your Umami Analytics to any MCP client to derive insights from natural language.

Extract palettes from images, generate harmonies, gradients, random palettes; Check WCAG and APCA contrast; Suggest nearest passing OkLCH lightness; Simulate color-blindness; Convert and sort colors across formats (hex / RGB / HSL / OkLCH / …)

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

A Code Indexing MCP Server that connects AI coding assistants to external codebases, providing accurate and up-to-date code snippets to reduce mistakes and hallucinations.

MCP server for local-first code intelligence, providing structural code graph, semantic search, and impact analysis to AI agents.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.