"Python context management and dependency solving in ComfyUI" matching MCP servers:

Enables AI agents to generate anime-style images using ComfyUI and Anima models, with MCP support for native image display in chat clients.

A local MCP server that enables AI assistants to control ComfyUI on a computer for image generation via Operit on a mobile device.

Python MCP server for SolidWorks automation with 109 tools covering the full CAD lifecycle. Enables AI-assisted design workflows through COM automation on Windows.

Enables Claude or any MCP client to drive a live SOLIDWORKS session through its COM API, modeling parts, building assemblies with mates, checking interferences and machining feasibility, and exporting STEP or DXF files. It also exposes a local semantic index of the SOLIDWORKS API so the model can look up signatures, enums, and official examples before running arbitrary Python against the session.

Enables AI coding clients to turn Lanhu design drafts into implementation context, including HTML/CSS or Tailwind output, sliced asset mappings, design tokens, preview images, and downstream implementation guidance.

A Model Context Protocol (MCP) server that enhances Figma design integration by adding element position information to API responses, enabling AI assistants to better understand spatial relationships and convert designs to code more accurately.

Converts Lanhu design URLs into AI-ready implementation context including HTML+CSS (Tailwind), image downloads, design tokens, and guidance.

Loads your project's Tailwind CSS config and exposes tools for AI agents to query actual design tokens and validate class names, preventing hallucination of non-existent utilities.

A read-only MCP server that extracts actual Figma prototype flows, transitions, and per-screen interactions so agents can see navigational behavior rather than infer it. It reports explicit source and destination IDs with warnings for unresolved or ambiguous destinations, without guessing or writing back to Figma.

Converts Figma designs into structured code context with token-aware styling, enabling AI agents to generate production-level frontend code.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

An MCP server that gives AI coding tools access to Figma design data for accurate one-shot implementation of designs.

An MCP server that gives AI coding agents access to Figma design data, enabling pixel-perfect implementation of designs through structured data extraction, image downloads, and design token retrieval.

Exposes tools to ingest FigJam boards, retrieve context summaries, and answer free-form questions about the board content.

Converts Figma design data into structured semantic analysis JSON and screenshots for AI agents to use in design-to-code workflows.

Enables driving Inkscape headlessly from an MCP client, with verified SVG editing, rendering, optimization, and animation tools.

Enables AI agents to programmatically create, inspect, edit, validate, and headlessly render traditional 2D hand-drawn animation projects, including frames, layers, audio, camera keyframes, spritesheets, and video or GIF exports.

Enables AI clients to inspect, visualize, modify, launch, and manage Autodesk BIM models, views, families, and documents through a local authenticated bridge, including direct code execution.

Enables AI coding agents such as Cursor to fetch, simplify, and translate Figma layout and styling data so they can implement designs accurately in code.

Gives AI coding agents like Cursor access to Figma file, frame, and group data, simplifying and translating Figma API responses into concise layout and styling context so designs can be implemented accurately in any framework in one shot.

Enables AI agents to extract design systems, analyze components, and maintain design-code consistency from Figma files, providing intelligent component analysis and accessibility compliance.

Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.

Enables AI coding agents such as Cursor to access Figma file, frame, and group data, simplifying Figma API responses into relevant layout and styling context so designs can be implemented accurately in code.

Enables AI coding agents to retrieve simplified Figma layout and styling data from files, frames, or groups so they can implement designs in code more accurately.

Enables Cursor to access Figma design data via MCP, allowing it to fetch simplified layout and styling information to accurately implement designs from Figma files.

Enables an MCP-capable AI client to drive a locally installed, licensed Autodesk Inventor through its COM API for local modeling tasks. It supports creating and updating a rectangular plate and a parametric quickchanger concept assembly, opening and inspecting parts and assemblies, and returning viewport previews.

Enables AI clients to read design pages, screenshots, original assets, styles, and workflows from Lanhu, Figma, and Mockplus, inspect elements, download resources, and build local page-flow maps.

Enables AI coding agents to access Figma design data, including file, frame, and group metadata, so they can implement designs accurately in code. It simplifies and translates Figma API responses into relevant layout and styling information.

Enables AI coding agents such as Cursor to access simplified Figma layout and styling data from file, frame, or group links so they can implement designs more accurately in code.

Local MCP server inside 8 Autodesk apps (Revit, AutoCAD, Civil 3D, Advance Steel, Navisworks, Inventor, 3ds Max, Robot; 2023–2027): 480+ read/write actions, one-click setup for Claude, ChatGPT/Codex and Cursor. Commercial, free 14-day trial. Formerly HMK Pilot.