Whatsupdoc
Raspe cualquier documentación del desarrollador y guárdelo localmente como un archivo de Markdown utilizando el MCP de Anthrope para estandarizar la comunicación entre la CLI y el servidor de documentación
0
Github Watches
1
Github Forks
2
Github Stars
WhatsUpDoc (downmarked)
A command-line tool for fetching and storing developer documentation locally using the Model Context Protocol (MCP).
Features
- Fetch documentation from any website and convert it to Markdown
- Save documentation to any location on your system
- Target specific content using CSS selectors
- Recursively fetch linked documentation pages
- Split documentation by headers into separate files
- Uses the Model Context Protocol (MCP) for standardized communication
Installation
# Install globally
npm install -g downmarked
# Or use with npx
npx downmarked fetch https://reactjs.org/docs/getting-started.html
Usage
Basic Usage
downmarked fetch <url>
This will prompt you for an output location and save the documentation as Markdown.
Options
# Fetch documentation with specific options
downmarked fetch https://reactjs.org/docs/getting-started.html \
-o ~/Documents/react-docs.md \
-s "main" \
-r \
-d 2 \
--split
Available Options
| Option | Description |
|---|---|
-o, --output <path> |
Output path (absolute or relative) |
-s, --selector <selector> |
CSS selector to target specific content |
-r, --recursive |
Recursively fetch linked documentation pages |
-d, --max-depth <number> |
Maximum depth for recursive fetching (default: 3) |
--split |
Split documentation by headers into separate files |
Examples
Fetch React Documentation
# Save React documentation to a specific location
downmarked fetch https://reactjs.org/docs/getting-started.html -o ~/Documents/react-docs.md
# Target only the main content area
downmarked fetch https://reactjs.org/docs/getting-started.html -s "main"
# Recursively fetch linked pages up to 2 levels deep
downmarked fetch https://reactjs.org/docs/getting-started.html -r -d 2
Fetch Python Documentation
# Save Python documentation
downmarked fetch https://docs.python.org/3/tutorial/index.html -o python-tutorial.md
How It Works
WhatsUpDoc (downmarked) uses the Model Context Protocol (MCP) to standardize communication between the CLI and the documentation server. The tool:
- Fetches HTML content from the specified URL
- Parses the HTML using Cheerio
- Converts the HTML to Markdown using Turndown
- Saves the Markdown to the specified location
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
- Model Context Protocol (MCP) for providing the communication framework
- Turndown for HTML to Markdown conversion
- Cheerio for HTML parsing
相关推荐
I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.
I find academic articles and books for research and literature reviews.
Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.
Confidential guide on numerology and astrology, based of GG33 Public information
Advanced software engineer GPT that excels through nailing the basics.
Emulating Dr. Jordan B. Peterson's style in providing life advice and insights.
Your go-to expert in the Rust ecosystem, specializing in precise code interpretation, up-to-date crate version checking, and in-depth source code analysis. I offer accurate, context-aware insights for all your Rust programming questions.
Converts Figma frames into front-end code for various mobile frameworks.
Descubra la colección más completa y actualizada de servidores MCP en el mercado. Este repositorio sirve como un centro centralizado, que ofrece un extenso catálogo de servidores MCP de código abierto y propietarios, completos con características, enlaces de documentación y colaboradores.
La aplicación AI de escritorio todo en uno y Docker con trapo incorporado, agentes de IA, creador de agentes sin código, compatibilidad de MCP y más.
Manipulación basada en Micrypthon I2C del expansor GPIO de la serie MCP, derivada de AdaFruit_MCP230xx
Plataforma de automatización de flujo de trabajo de código justo con capacidades de IA nativas. Combine el edificio visual con código personalizado, auto-anfitrión o nube, más de 400 integraciones.
🧑🚀 全世界最好的 llM 资料总结(数据处理、模型训练、模型部署、 O1 模型、 MCP 、小语言模型、视觉语言模型) | Resumen de los mejores recursos del mundo.
Espejo dehttps: //github.com/agentience/practices_mcp_server
Una lista curada de servidores de protocolo de contexto del modelo (MCP)
Reviews
user_08ZVJAwA
I have been using the Singapore LTA MCP Server by arjunkmrm and it has significantly improved my workflow. The seamless integration and reliability of the server are unmatched. It's user-friendly and the support from the author is excellent. Highly recommend this server to anyone looking for efficiency and stability in their applications. Check it out at https://mcp.so/server/sg-lta-mcp/arjunkmrm!