Jina AI MCP Server

An MCP server that provides access to Jina AI's powerful web services through Claude. This server implements three main tools:

Web page reading and content extraction
Web search
Fact checking/grounding

Features

Tools

`read_webpage`

Extract content from web pages in a format optimized for LLMs
Supports multiple output formats (Default, Markdown, HTML, Text, Screenshot, Pageshot)
Options for including links and images
Ability to generate alt text for images
Cache control options

`search_web`

Search the web using Jina AI's search API
Configurable number of results (default: 5)
Support for image retention and alt text generation
Multiple return formats (markdown, text, html)
Returns structured results with titles, descriptions, and content

`fact_check`

Fact-check statements using Jina AI's grounding engine
Provides factuality scores and supporting evidence
Optional deep-dive mode for more thorough analysis
Returns references with key quotes and supportive/contradictory classification

Setup

Prerequisites

You'll need a Jina AI API key to use this server. Get one for free at https://jina.ai/

Installation

There are two ways to use this server:

Installing via Smithery

To install Jina AI for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install jina-ai-mcp-server --client claude

Option 1: NPX (Recommended)

Add this configuration to your Claude Desktop config file:

{
  "mcpServers": {
    "jina-ai-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "jina-ai-mcp-server"
      ],
      "env": {
        "JINA_API_KEY": "<YOUR_KEY>"
      }
    }
  }
}

Option 2: Local Installation

Clone the repository
Install dependencies:

npm install

Build the server:

npm run build

Add this configuration to your Claude Desktop config:

{
  "mcpServers": {
    "jina-ai-mcp-server": {
      "command": "node",
      "args": [
        "/path/to/jina-ai-mcp-server/dist/index.js"
      ],
      "env": {
        "JINA_API_KEY": "<YOUR_KEY>"
      }
    }
  }
}

Config File Location

On MacOS:

~/Library/Application Support/Claude/claude_desktop_config.json

On Windows:

%APPDATA%/Claude/claude_desktop_config.json

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

API Response Types

All tools return structured JSON responses that include:

Status codes and metadata
Formatted content based on the requested output type
Usage information (token counts)
When applicable: images, links, and additional metadata

For detailed schema information, see schemas.ts.