Docs2prompt
An MCP server that converts documentation into LLM-friendly prompts
rating : 2 points
downloads : 5.9K
What is the docs2prompt MCP server?
The docs2prompt MCP server is a tool based on the Model Context Protocol (MCP). It can extract documentation content from GitHub repositories or dedicated websites and convert it into prompts suitable for use with large language models (LLMs).How to use the docs2prompt MCP server?
First, you need to install the UV tool. Then, clone this repository and configure the client. Finally, run the server by specifying the path to start using it.Use cases
Suitable for enterprises and individual developers who need to extract information from technical documentation and generate high-quality LLM prompts.Main Features
Support for GitHub documentation extraction
It can automatically fetch documentation content from GitHub repositories and perform preprocessing.
Generate LLM-friendly prompts
Generate structured prompts based on the extracted documentation content for subsequent model training or inference tasks.
Multi-client compatibility
Supports multiple MCP clients (such as Cursor, Claude, etc.) for easy integration into existing workflows.
Advantages
Quickly generate high-quality prompts
Support multiple documentation sources
Easy to integrate with other MCP clients
Limitations
Depends on a GitHub access token
Requires a certain network environment
How to Use
Install the UV tool
Ensure that the UV tool is installed on the system. It can be quickly installed via the official script.
Clone the repository
Clone the code repository of the docs2prompt MCP server from GitHub.
Configure the client
Add the server address and relevant environment variables to the MCP client configuration.
Usage Examples
Extract GitHub documentation to generate prompts
Extract documentation from a specific GitHub repository and generate prompts.
Frequently Asked Questions
How to obtain a GitHub access token?
What should I do if the server fails to run?
Related Resources
docs2prompt GitHub repository
View the project source code and documentation.
Model Context Protocol official website
Learn about the details of the MCP protocol.
UV tool installation guide
Learn how to install the UV tool.

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
23.8K
5 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
15.7K
4.3 points

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
15.9K
4.5 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
44.2K
4.3 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
20.3K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
45.1K
4.5 points

Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
16.0K
4.5 points

Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
30.7K
4.8 points

