
JinaAI Grounding
โ 1from spences10
Enhances LLM responses with factual, real-time web content using Jina AI's grounding capabilities.
mcp-jinaai-grounding
โ ๏ธ 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This repository is no longer maintained.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
- ๐ Advanced web content grounding through Jina.ai Grounding API
- ๐ Real-time content verification and fact-checking
- ๐ Comprehensive web content analysis
- ๐ Clean format optimized for LLMs
- ๐ฏ Precise content relevance scoring
- ๐๏ธ Built on the Model Context Protocol
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 devPublishing
- Update version in package.json
- Build the project:
pnpm run build- Publish to npm:
pnpm run release{
"mcpServers": {
"jinaai-grounding": {
"command": "wsl.exe",
"args": [
"bash",
"-c",
"JINAAI_API_KEY=your-jinaai-api-key npx mcp-jinaai-grounding"
]
}
}
}Before it works, you'll need: JINAAI_API_KEY
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)
No common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.
Licensed under MITโ you can use, modify, and redistribute it under that license's terms.
License
MIT License - see the LICENSE file for details.