mcpField
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fetch-mcp

fetch-mcp

Local
github.com/egoistBrowser Automation157Updated 82w ago

About fetch-mcp

fetch-mcp is an MCP server for fetching web page content and YouTube video transcripts. It can run over stdio, SSE or streamable HTTP, and suits users who want AI assistants to read web pages or video text.

Key features

  1. 01Fetch content from URLs
  2. 02Return Markdown or HTML output
  3. 03Retrieve YouTube video transcripts
  4. 04Support stdio, SSE and HTTP transports

Use cases

  1. 01Letting an AI assistant read and summarize web pages
  2. 02Extracting YouTube transcripts for analysis or notes
  3. 03Supplying web data to an LLM in browser-related workflows

MCP support

fetch-mcp is an MCP server that exposes the fetch_url and fetch_youtube_transcript tools to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"fetch-mcp-egoist": {
"command": "npx",
"args": [
"-y",
"fetch-mcp"
]
}
}
}
Run commandnpx -y fetch-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmfetch-mcp

Tools

2

Saved tool list · updated 3w ago

ParameterTypeRequiredDescription
urlstringYesThe URL to fetch
rawboolean|nullNoReturn raw HTML instead of Markdown for HTML pages
max_lengthnumberNoThe max length of the content to return
start_indexnumberNoThe starting index of content to return

Details

From the project README

fetch-mcp

An MCP server for fetching URLs / Youtube video transcript.

This project is sponsored by ChatWise, an all-in-one LLM chatbot with first-class MCP support.

Usage

# stdio server
npx -y fetch-mcp

# sse server
npx -y fetch-mcp --sse

# streamable http server at /mcp
npx -y fetch-mcp --http
# custom endpoint
npx -y fetch-mcp --http /my-mcp

Tools

fetch_url

Fetch URL, can return HTML or Markdown (default).

fetch_youtube_transcript

Fetch Youtube transcript.

License

MIT.

Comments

Markdown supported

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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.