Jina AI Search

An MCP server for Jina AI, providing tools for embeddings, reranking, and generation. This is the Node.js version.

This server provides the following tools, which are direct interfaces to the Jina AI Search Foundation APIs:

- embeddings: Creates an embedding vector representing the input text.
- rerank: Reranks a list of documents based on a query.
- read: Extracts clean, LLM-friendly content from a single website URL.
- search: Performs a web search and returns LLM-friendly results.
- deepsearch: Combines web searching, reading, and reasoning for comprehensive investigation.
- segment: Splits text into semantic chunks or counts tokens.
- classify: Performs zero-shot classification for text.
- get_help: Returns the full Jina AI API documentation used to build this server.

To connect this server to your MCP-compatible client (like Cursor, shell-ai, etc.), you first need to publish this package to NPM or install it from a local path.

Once the package is published on NPM, you can configure your client to use it withnpx. Create a.envfile with yourJINA_API_KEYin the directory where you run the client, or make sure the environment variable is set.

{ "jina-ai-server": { "command": "npx", "args": [ "jina-ai-mcp-server-nodejs" ], "env": { "JINA_API_KEY": "your_jina_api_key_here" } } }

Note:Passing the API key viaenvin the configuration is more secure than a global environment variable.
- Clone the repository.
- Install dependencies:

npm install

echo "JINA_API_KEY=your_jina_ai_api_key_here" > .env

To compile the TypeScript code to JavaScript:

The compiled output will be in thedistdirectory.

You can then run the compiled code with:

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