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Lanhu MCP Server

Lanhu MCP Server is a Python server built with FastMCP that exposes Lanhu requirements, design materials and team knowledge to AI assistants through the Model Context Protocol.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Lanhu MCP Server — OpenViST project profile in MCP & Tooling.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when an MCP-capable coding assistant needs access to Lanhu requirements or design resources as part of development, testing or design handoff.

Who it is for

  • Developers using MCP-capable AI coding assistants with Lanhu project materials.
  • Teams that want assistants to share requirements analysis and collaboration context.
  • Testers who want AI-assisted test scenarios and boundary-case analysis from requirements.

Documented uses

  • Extract and review Axure requirement pages, text and supported annotations.
  • Organize requirement analysis for development, testing or quick exploration.
  • Retrieve design previews, style information and downloadable assets for implementation work.
  • Share team knowledge and context across AI assistants through the project’s collaboration features.
Before you choose

Requirements & limits

  • The server requires a Lanhu cookie, which the setup guide says to obtain from the logged-in Lanhu web session.
  • The README specifies Python 3.10 or newer for source setup and names FastMCP as its framework.
  • An MCP-compatible client is needed to consume the server; the README lists several AI development tools as examples.
  • Design-derived HTML and CSS are references that require checking against original annotations and rendered output.
  • The project displays an MIT license.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install and configure from source

Prepare the server environment and configure its required Lanhu cookie.

Before you start

  • Python 3.10 or newer
  • Lanhu account access sufficient to obtain a web-session cookie
  • A shell on Linux or macOS, or Windows batch support

Steps

  1. Clone the repository and change into its directory.

  2. Run bash easy-install.sh on Linux or macOS, or easy-install.bat on Windows; the project says the installer installs dependencies and guides cookie configuration.

  3. For manual setup instead, create a Python virtual environment, install the project with pip install -e ., install Playwright Chromium, copy .env.example to .env, and set LANHU_COOKIE to your cookie.

Expected outcome

The project dependencies and required Lanhu cookie configuration are prepared for the server setup; these steps alone do not configure an AI client or demonstrate a running workflow.

Guide limitations

  • The README's manual setup commands differ by operating system; use the appropriate documented commands.
  • A Lanhu cookie is required. Feishu webhook configuration is optional and is not needed for this setup goal.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
9 October 2026
Original website title
dsphper/lanhu-mcp · Official homepage title · retained in its source language
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