Jina.ai Grounding MCP Server
Integrates Jina.ai's Grounding API with LLMs for real-time, fact-based web content grounding and analysis, enhancing LLM responses with precise, verified information.
spences10
Tools
ground_statement
Ground a statement using real-time web search results to check factuality. When providing URLs via the references parameter, ensure they are publicly accessible and contain relevant information about the statement. If the URLs do not contain the necessary information, try removing the URL restrictions to search the entire web.
README
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This repository is no longer maintained.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.
<a href="https://glama.ai/mcp/servers/urkuhet67l"> <img width="380" height="200" src="https://glama.ai/mcp/servers/urkuhet67l/badge" /> </a>
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 contentno_cache
(boolean, optional): Bypass cache for fresh results. Defaults to falseformat
(string, optional): Response format ("json" or "text"). Defaults to "text"token_budget
(number, optional): Maximum number of tokens for this requestbrowser_locale
(string, optional): Browser locale for rendering contentstream
(boolean, optional): Enable stream mode for large pages. Defaults to falsegather_links
(boolean, optional): Gather all links at the end of response. Defaults to falsegather_images
(boolean, optional): Gather all images at the end of response. Defaults to falseimage_caption
(boolean, optional): Caption images in the content. Defaults to falseenable_iframe
(boolean, optional): Extract content from iframes. Defaults to falseenable_shadow_dom
(boolean, optional): Extract content from shadow DOM. Defaults to falseresolve_redirects
(boolean, optional): Follow redirect chains to final URL. Defaults to true
Development
Setup
- Clone the repository
- Install dependencies:
pnpm install
- Build the project:
pnpm run build
- Run in development mode:
pnpm run dev
Publishing
- Update version in package.json
- Build the project:
pnpm run build
- 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
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