What is Mcp Jinaai Search

mcp-jinaai-search is a Model Context Protocol (MCP) server designed to integrate Jina.ai’s Search API with large language models (LLMs), providing efficient web search capabilities optimized for retrieving clean, LLM-friendly content from the web.

Use cases

Use cases include academic research where users need to gather information quickly, content generation for blogs or articles, data analysis for extracting insights from web content, and enhancing chatbot capabilities with accurate and relevant information.

How to use

To use mcp-jinaai-search, configure your MCP client with the appropriate settings, including your Jina.ai API key. You can set it up for different environments such as Cline or WSL, and then utilize the search API to retrieve content by sending a search query.

Key features

Key features include advanced web search through the Jina.ai Search API, fast content retrieval, clean text extraction while preserving structure, content optimized for LLMs, support for various content types, configurable caching, optional image and link gathering, localization support, and token budget control for response size.

Where to use

mcp-jinaai-search can be used in various fields such as research, content creation, data analysis, and any application requiring efficient web search and content retrieval tailored for LLMs.

mcp-jinaai-search

⚠️ Notice

This repository is no longer maintained.

The functionality of this tool is now available in mcp-omnisearch, which combines multiple MCP tools in one unified package.

Please use mcp-omnisearch instead.

A Model Context Protocol (MCP) server for integrating Jina.ai’s Search
API with LLMs. This server provides efficient and comprehensive web
search capabilities, optimised for retrieving clean, LLM-friendly
content from the web.

Features

• 🔍 Advanced web search through Jina.ai Search API
• 🚀 Fast and efficient content retrieval
• 📄 Clean text extraction with preserved structure
• 🧠 Content optimised for LLMs
• 🌐 Support for various content types including documentation
• 🏗️ Built on the Model Context Protocol
• 🔄 Configurable caching for performance
• 🖼️ Optional image and link gathering
• 🌍 Localisation support through browser locale
• 🎯 Token budget control for response size

Configuration

This server requires configuration through your MCP client. Here are
examples for different environments:

Cline Configuration

Add this to your Cline MCP settings:

{
  "mcpServers": {
    "jinaai-search": {
      "command": "node",
      "args": [
        "-y",
        "mcp-jinaai-search"
      ],
      "env": {
        "JINAAI_API_KEY": "your-jinaai-api-key"
      }
    }
  }
}

Claude Desktop with WSL Configuration

For WSL environments, add this to your Claude Desktop configuration:

{
  "mcpServers": {
    "jinaai-search": {
      "command": "wsl.exe",
      "args": [
        "bash",
        "-c",
        "JINAAI_API_KEY=your-jinaai-api-key npx mcp-jinaai-search"
      ]
    }
  }
}

Environment Variables

The server requires the following environment variable:

• JINAAI_API_KEY: Your Jina.ai API key (required)

API

The server implements a single MCP tool with configurable parameters:

search

Search the web and get clean, LLM-friendly content using Jina.ai
Reader. Returns top 5 results with URLs and clean content.

Parameters:

• query (string, required): Search query
• format (string, optional): Response format (“json” or “text”).
  Defaults to “text”
• no_cache (boolean, optional): Bypass cache for fresh results.
  Defaults to false
• token_budget (number, optional): Maximum number of tokens for this
  request
• browser_locale (string, optional): Browser locale for rendering
  content
• stream (boolean, optional): Enable stream mode for large pages.
  Defaults to false
• gather_links (boolean, optional): Gather all links at the end of
  response. Defaults to false
• gather_images (boolean, optional): Gather all images at the end of
  response. Defaults to false
• image_caption (boolean, optional): Caption images in the content.
  Defaults to false
• enable_iframe (boolean, optional): Extract content from iframes.
  Defaults to false
• enable_shadow_dom (boolean, optional): Extract content from shadow
  DOM. Defaults to false
• resolve_redirects (boolean, optional): Follow redirect chains to
  final URL. Defaults to true

Development

Setup

1. Clone the repository
2. Install dependencies:

pnpm install

3. Build the project:

pnpm run build

4. Run in development mode:

pnpm run dev

Publishing

1. Create a changeset:

pnpm changeset

2. Version the package:

pnpm version

3. Build and publish:

pnpm release

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see the LICENSE file for details.

Acknowledgments

• Built on the
  Model Context Protocol
• Powered by Jina.ai Search API