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Jina AI MCP Server

by Sheshiyer
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote
MIT License
4

Jina AI MCP Server

A Model Context Protocol (MCP) server that provides seamless integration with Jina AI's neural search capabilities. This server enables semantic search, image search, and cross-modal search functionalities through a simple interface.

🚀 Features

  • Semantic Search: Find semantically similar documents using natural language queries

  • Image Search: Search for visually similar images using image URLs

  • Cross-Modal Search: Perform text-to-image or image-to-text searches

Related MCP server: Jina Web Search MCP

📋 Prerequisites

  • Node.js 16 or higher

  • A Jina AI account and API key (Get one here)

  • MCP-compatible environment (e.g., Cline)

🛠️ Installation

  1. Clone the repository:

git clone <repository-url> cd jina-ai-mcp

  1. Install dependencies:

npm install

  1. Create a .env file with your Jina AI API key:

JINA_API_KEY=your_api_key_here

  1. Build the server:

npm run build

⚙️ Configuration

Add the following configuration to your MCP settings file:

{ "mcpServers": { "jina-ai": { "command": "node", "args": [ "/path/to/jina-ai-mcp/build/index.js" ], "env": { "JINA_API_KEY": "your_api_key_here" } } } }

🔍 Available Tools

1. Semantic Search

Perform semantic/neural search on text documents.

use_mcp_tool({ server_name: "jina-ai", tool_name: "semantic_search", arguments: { query: "search query text", collection: "your-collection-name", limit: 10 // optional, defaults to 10 } })

2. Image Search

Search for similar images using an image URL.

use_mcp_tool({ server_name: "jina-ai", tool_name: "image_search", arguments: { imageUrl: "https://example.com/image.jpg", collection: "your-collection-name", limit: 10 // optional, defaults to 10 } })

3. Cross-Modal Search

Perform text-to-image or image-to-text search.

use_mcp_tool({ server_name: "jina-ai", tool_name: "cross_modal_search", arguments: { query: "a beautiful sunset", // or image URL for image2text mode: "text2image", // or "image2text" collection: "your-collection-name", limit: 10 // optional, defaults to 10 } })

📝 Response Format

All search tools return results in the following format:

{ content: [ { type: "text", text: JSON.stringify({ results: [ { id: string, score: number, data: Record<string, any> } ] }, null, 2) } ] }

🔐 Error Handling

The server handles various error cases:

  • Invalid API key

  • Missing or invalid parameters

  • API rate limits

  • Network errors

  • Invalid collection names

All errors are properly formatted and returned with appropriate error codes and messages.

🤝 Contributing

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

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

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