What is the main purpose of this server?
It lets LLMs autonomously fetch and explore web content, especially documentation, by recursively following same‑domain links to gather complete context on a topic.
@wolfyy970
Basic information
MCP server for fetching web page content with recursive exploration capability
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"docs-fetch": {
"command": "node",
"args": [
"/path/to/docs-fetch-mcp/build/index.js"
],
"env": {
"MCP_TRANSPORT": "pipe"
}
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
An MCP server that enables LLMs to fetch web content with recursive exploration. It retrieves clean, readable text from web pages and autonomously follows same-domain links up to a specified depth, making it ideal for learning topics by exploring documentation.
Install via npm and build the project. Configure your MCP client (e.g., Claude Desktop) with the node command pointing to the built index.js. The server exposes a single tool fetch_doc_content which accepts a URL and optional depth (1–5), returning page content and discovered links.
It lets LLMs autonomously fetch and explore web content, especially documentation, by recursively following same‑domain links to gather complete context on a topic.
Node.js, npm, and the packages `@modelcontextprotocol/sdk`, `puppeteer`, and `axios`. Puppeteer is used as a fallback for complex pages.
Clone the repo, run `npm install` and `npm run build`, then add the server to your MCP client’s configuration with the `node` command pointing to `build/index.js` and set `MCP_TRANSPORT` to `"pipe"`.
The depth parameter accepts 1 to 5, with a default of 1. Higher values explore more linked pages within the same domain.
Yes. It implements global timeout handling, graceful error recovery for network issues, and returns partial results even if some pages fail.

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