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Docs To Llm MCP Server

@Rybens92

基本信息

关于 Docs To Llm MCP Server

暂无概览

Docs To Llm MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "docs-to-llm": {
      "command": "python",
      "args": [
        "/your/path/to/this/mcp/server/src/server.py"
      ],
      "disabled": false
    }
  }
}

Docs To Llm MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Docs To Llm?

Docs To Llm is an MCP server that processes technical documentation into llm.txt format. It generates two files — a short version with titles and links, and a full version with complete content — for use as context in LLM environments like Cursor, Windsurf, Cline, or Roo Code.

How to use Docs To Llm?

Clone the repository and install dependencies with uv pip install -r requirements.txt or pip install -r requirements.txt. Configure the server in your MCP settings (e.g., mcp_settings.json) with the command python and the path to src/server.py. Invoke the process_documentation tool to crawl a documentation URL, providing the URL, library name, and output directory. The server returns paths to the generated llm_{library_name}_short.txt and llm_{library_name}_full.txt files.

Key features of Docs To Llm

  • Automatic detection of documentation navigation sections
  • Conversion of relative URLs to absolute URLs
  • Removal of unnecessary HTML elements (scripts, styles, menus)
  • Progress reporting during processing
  • Detailed error logging
  • Smart scoring system to find relevant documentation links
  • Fallback mechanisms when automatic detection fails
  • Sanitized filenames based on library names

Use cases of Docs To Llm

  • Generate concise documentation context for LLM-powered code assistants like Cursor or Windsurf
  • Create a full-text local copy of a library's docs for offline analysis
  • Produce short link-only summaries of large documentation sites
  • Integrate documentation ingestion into automated build or tooling pipelines
  • Feed structured documentation into Roo Code or Cline for context-aware prompts

常见问题

1

What Python version is required?

Python 3.7 or higher is required.

2

How do I install the dependencies?

Use `uv pip install -r requirements.txt` (recommended) or `pip install -r requirements.txt`.

3

Where are the output files saved?

You specify the output directory via the `txt_save_path` parameter in the `process_documentation` tool call. The server creates two files there.

4

How do I configure Docs To Llm in Cline or Roo Code?

Add a `docs-to-llm` entry to your `mcp_settings.json` with command `python` and args pointing to the full path of `src/server.py`.

5

What tool does the server expose?

The server provides one tool: `process_documentation`, which accepts a URL, library name, and save path, and returns success status and file paths.

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