Ant Design MCP Server
Fetches and structures Ant Design v4 component documentation into JSON format, enabling AI agents to search, analyze, and retrieve component metadata, APIs, and examples.
README
Ant Design MCP Server (Python)
This Model Context Protocol (MCP) server fetches and structures Ant Design v4 (Chinese) component documentation into JSON so AI agents can perform analysis.
Features
- Fetch overview page and individual component pages.
- Extract component metadata: name, description, examples.
- Classify API tables automatically (props / events / methods / other).
- Cache fetched HTML locally.
- Export all components into a single JSON file.
- MCP tools exposed over JSON-RPC stdio.
Tools
- list_components(force?)
- get_component(name, force?)
- search_components(query)
- export_all(force?, filepath?)
Environment Setup
Choose one method:
venv (built-in)
python -m venv .venv
source .venv/bin/activate
pip install -r src/antd_mcp/requirements.txt
pyenv + venv
brew install pyenv
pyenv install 3.11.8
pyenv local 3.11.8
python -m venv .venv
source .venv/bin/activate
pip install -r src/antd_mcp/requirements.txt
Conda
conda create -n antd-mcp python=3.11 -y
conda activate antd-mcp
pip install -r src/antd_mcp/requirements.txt
Run Server
python -m antd_mcp
# or
python src/antd_mcp/server.py
JSON-RPC Examples
# List tools
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | python -m antd_mcp
# List components
echo '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"list_components","arguments":{}}}' | python -m antd_mcp
# Get one component
echo '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"get_component","arguments":{"name":"Button"}}}' | python -m antd_mcp
# Search components
echo '{"jsonrpc":"2.0","id":4,"method":"tools/call","params":{"name":"search_components","arguments":{"query":"form"}}}' | python -m antd_mcp
# Export all component data
echo '{"jsonrpc":"2.0","id":5,"method":"tools/call","params":{"name":"export_all","arguments":{}}}' | python -m antd_mcp
Export Output
Default file: src/antd_mcp/exports/antd_components_all.json
Structure:
{
"generated_at": <timestamp>,
"count": <number_of_components>,
"components": [
{
"name": "Button",
"title": "Button 按钮",
"intro": [...],
"props": [...],
"events": [...],
"methods": [...],
"other_tables": [...],
"table_summary": {"props":1,"events":0,...},
"examples": [...],
"source_url": "https://4x.ant.design/..."
}
]
}
TODO / Roadmap
- More precise table classification rules (column semantics).
- Parallel fetching & retry with backoff.
- Version / language (en vs cn) selection.
- CLI wrapper.
- Optional rate limiting.
License
MIT (add if needed)
安装 (发布后)
pip install antd-mcp-server
安装后命令行入口:
antd-mcp --once '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'
本地构建与发布
# 构建
python -m build
# 上传到 PyPI
python -m twine upload dist/*
供 AI 工具使用的 mcp.json 示例
{
"version": 1,
"servers": {
"antd_mcp": {
"command": "antd-mcp",
"args": [],
"timeoutSeconds": 60
}
}
}
环境变量
ANTD_MCP_CACHE_DIR自定义缓存目录。MCP_PRETTY/MCP_COLOR控制输出格式。
版本
当前版本: 0.1.0
antd-mcp
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.