mcpField
J
Jina_fetch

Jina_fetch

Local
github.com/RoadMillionBrowser Automation0Updated 83w ago
Repository

About Jina_fetch

Jina_fetch is an MCP server that uses the Jina AI API to turn a URL into text formatted for LLM input. It offers a single URL-reading tool for MCP clients.

Key features

  1. 01Converts URLs into LLM-friendly text
  2. 02Reads a URL through the Jina AI API
  3. 03Returns processed page content

Use cases

  1. 01Preparing web pages for LLM processing
  2. 02Retrieving readable content from a URL

MCP support

Exposes a `reader` tool to MCP clients. The tool accepts a URL and returns its processed content.

Configuration

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

mcp.json · Universal config
{
  "mcpServers": {
    "jina-reader-roadmillion": {
      "command": "uvx",
      "args": [
        "mcp-jina-reader@latest"
      ]
    }
  }
}
Run commanduvx mcp-jina-reader@latest

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
pypimcp-jina-reader@latest

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

mcp-jina-reader MCP server

A standard MCP server that converts URLs into LLM-friendly inputs using Jina AI's API

Tools

The server implements one tool:

  • reader: Use Jina URL reader to process URLs and return LLM-friendly output
    • Requires "url" as a mandatory string parameter
    • Returns processed URL content

Quickstart

Install
Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

Development/Unpublished Servers Configuration ``` "mcpServers": { "mcp-jina-reader": { "command": "uv", "args": [ "--directory", "your-dir", "run", "mcp-jina-reader" ] } } ```
Published Servers Configuration ``` "mcpServers": { "mcp-jina-reader": { "command": "uvx", "args": [ "mcp-jina-reader" ] } } ```

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

  • Token: --token or UV_PUBLISH_TOKEN
  • Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD
Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory yourdir run mcp-jina-reader

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

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.