search-web

Jina AI▌

by joebuildsstuff

Jina AI enables ai powered search, content extraction, and fact-checking using natural language, making it the best ai s

Integrates with Jina AI's web services to enable web content extraction, search, and fact-checking through natural language interactions.

github stars

★ 29

GitHub npm

Multiple output formats availableBuilt-in fact-checking with evidenceLLM-optimized content extraction

best for

/ Research and content analysis
/ Fact-checking and verification
/ Web scraping and data extraction
/ Content creators needing web research

capabilities

/ Extract and format web page content
/ Search the web with structured results
/ Fact-check statements with evidence
/ Generate screenshots of web pages
/ Convert content to multiple formats
/ Generate alt text for images

what it does

Extracts content from web pages, searches the web, and fact-checks statements using Jina AI's services.

about

Jina AI is a community-built MCP server published by joebuildsstuff that provides AI assistants with tools and capabilities via the Model Context Protocol. Jina AI enables ai powered search, content extraction, and fact-checking using natural language, making it the best ai s It is categorized under search web.

how to install

You can install Jina AI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Jina AI is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

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.

Running evals

The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.

OPENAI_API_KEY=your-key  npx mcp-eval evals.ts index.ts