"How to generate HTML code from Figma design files" matching MCP servers:

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.

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

Enables AI agents to send HTML documents to a local viewer, where they are stored and displayed in a live web UI for browsing and searching.

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.

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

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.

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.

MCP server that indexes Markdown, Word, HTML, and PDF documents into a SQLite knowledge graph with CJK+Latin full-text search and cross-document reference tracking. Runs drift audits to surface stale policies, conflicting research claims, superseded ADRs, and undocumented code exports.

Gives AI assistants real-time access to web data with the ability to scrape any website, bypass anti-bot systems, extract structured data, and capture screenshots through enterprise-grade infrastructure.

A Model Context Protocol server that enables AI assistants to read from and write to Microsoft Excel files, supporting formats like xlsx, xlsm, xltx, and xltm.

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

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.

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