JinaAI Grounding

Integrates JinaAI's content extraction and analysis capabilities for web scraping, documentation parsing, and text analysis tasks.

Installation Instructions

README: https://github.com/spences10/mcp-jinaai-grounding

mcp-jinaai-grounding

⚠️ 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This repository is no longer maintained.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 Grounding API with LLMs. This server provides efficient and comprehensive web content grounding capabilities, optimized for enhancing LLM responses with factual, real-time web content.

Features

• 🌐 Advanced web content grounding through Jina.ai Grounding API
• 🚀 Real-time content verification and fact-checking
• 📚 Comprehensive web content analysis
• 🔄 Clean format optimized for LLMs
• 🎯 Precise content relevance scoring
• 🏗️ Built on the Model Context Protocol

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

Environment Variables

The server requires the following environment variable:

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

API

The server implements MCP tools for grounding LLM responses with web content:

ground_content

Ground LLM responses with real-time web content using Jina.ai Grounding.

Parameters:

• query (string, required): The text to ground with web content
• no_cache (boolean, optional): Bypass cache for fresh results. Defaults to false
• format (string, optional): Response format ("json" or "text"). Defaults to "text"
• 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. Update version in package.json
2. Build the project:

pnpm run build

3. Publish to npm:

pnpm run 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 Grounding API