"Information about Lanhu" matching MCP servers:

Converts a Lanhu design page into a Unity UGUI prefab YAML snapshot, enabling Unity developers to generate UI prefabs from Lanhu designs.

Enables AI coding tools to read Lanhu design data and automate Design to Code, including project browsing, layer tree extraction, DDS semantic components, and code generation.

Provides AI coding agents with structured access to Lanhu design data, enabling direct inspection of artboards, extraction of pixel-perfect layer styles and CSS attributes, and downloading of design assets without vision token overhead.

Enables AI coding assistants to directly access Lanhu design drafts, generate frontend code, parse PRDs, and download design assets.

Enables AI to directly read and analyze Lanhu design drafts and requirement documents to generate HTML, CSS, and structural analyses. It allows users to extract design slices and process prototype pages directly within AI clients.

Read-only MCP server that converts Lanhu project/design links into design context consumable by Codex or other AI agents.

Fetches Lanhu UI design specs and assets with minimal tokens, enabling coding agents to implement high-fidelity UI by providing precise coordinates, styles, and downloaded resources.

Enables AI assistants to read Lanhu design collaboration content: extracting and analyzing Axure prototype pages, downloading UI designs and slices, and converting design specs into HTML+CSS for implementation. It also provides a shared team message board so multiple AI tools can reuse requirement analyses and knowledge across projects.

Enables AI assistants to read Lanhu design specs — layer trees with per-layer CSS, screenshots, downloadable slices, and review comments — so they can restore UI and generate React/Vue/mini-program code without manual measuring or asset hunting.

Parses Lanhu design files into structured layer trees with detailed visual properties, supports slice downloads, requirement documents, and team collaboration features.

Enables AI assistants to read Lanhu requirements and design handoffs, extract pages, annotations, screenshots, design parameters, and image assets, and share team knowledge through a collaborative message board.

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

Connects AI assistants to Lanhu design collaboration platform for analyzing Axure prototypes, downloading UI designs, and enabling team knowledge sharing through a collaborative message board that breaks AI IDE silos.

Enables AI assistants to connect to the Lanhu design collaboration platform, allowing them to analyze requirement documents, inspect UI designs with detailed parameters, download design slices, and share team knowledge through a collaborative message board.

A read-only MCP server for reading and analyzing Lanhu (Blue Lake) design projects, providing tools to retrieve design lists, previews, node trees, schemas, and exportable resources.

Exposes information about Z-Image AI image generation and editing platform, including styles, pricing, and official links, for MCP-compatible AI clients.

AI-powered MCP server for analyzing UI designs and bug reports from Lanhu and Zentao platforms.

Use Claude to control or ask questions about your Altium project.

Use Claude to control or ask questions about your Altium project.

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.

MCP server providing AI assistants with comprehensive documentation about @deay/ui components, including props, examples, best practices, and Figma design specifications.

Enables coding agents to read ground truth about a React design system — components, props, cva variants, tokens and docs — over MCP so they write UI that matches it. It also exposes a check_ui linter agents run on their own output, returning rule ids, locations and concrete fixes before review.

thicken turns photos of a real object into a GLB model at its real size and its metadata as JSON, read off the object by vision models and looked up in public catalogs. What it knows about each kind of object lives in a profile: a few come with thicken, and you can add your own.

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

Exposes Levit design system (GDS) metadata to AI coding tools, enabling queries about color tokens and component usage via natural language.

Enables controlling a local Blender instance through natural language or code, allowing arbitrary Python/bpy execution and querying scene or object information via MCP.

Enables AI clients to search a library of 2,800+ science illustrations, fetch SVG content and metadata, and download icons locally, with category/license filtering and attribution information.

Enables Claude AI to extract design information from Figma files and create or update designs via a Figma plugin, supporting both readonly and write modes.

Local MCP server for parsing Sketch exported HTML zip archives and extracting design structure information.

Enables AI assistants to create, edit, and export IFC5/IFCX building information models through natural language, handling spatial structure, elements, geometry, metadata, validation, and export.