MCP

🚀 Jina AI Remote MCP Server

This is a remote Model Context Protocol (MCP) server that offers access to Jina Reader, Embeddings, and Reranker APIs. It comes with a set of tools for URL-to-markdown conversion, web search, image search, and embeddings/reranker operations.

✨ Features

Tool Details

⚠️ Important Note

Optional tools work without an API key but have rate limits. For higher rate limits and better performance, use a Jina API key. You can get a free Jina API key from https://jina.ai

🚀 Quick Start

For clients that support remote MCP server

{
  "mcpServers": {
    "jina-mcp-server": {
      "url": "https://mcp.jina.ai/sse",
      "headers": {
        "Authorization": "Bearer ${JINA_API_KEY}" // optional
      }
    }
  }
}

For clients that do not support remote MCP server yet

You need mcp-remote, a local proxy to connect to the remote MCP server.

{
  "mcpServers": {
    "jina-mcp-server": {
      "command": "npx",
      "args": [
        "mcp-remote", 
        "https://mcp.jina.ai/sse",
        // optional bearer token
        "--header",
        "Authorization: Bearer ${JINA_API_KEY}"
        ]
    }
  }
}

🔧 Troubleshooting

I got stuck in a tool calling loop - what happened?

This is a common issue with LMStudio when the default context window is 4096 and you're using a thinking model like gpt-oss-120b or qwen3-4b-thinking. As the thinking and tool calling continue, once you hit the context window limit, the AI starts losing track of the beginning of the task. That's how it gets trapped in this rolling context window.

The solution is to load the model with enough context length to contain the full tool calling chain and thought process.

📚 Documentation

Local Development

# Clone the repository
git clone https://github.com/jina-ai/MCP.git
cd MCP

# Install dependencies
npm install

# Start development server
npm run start

Deploy to Cloudflare Workers

This will deploy your MCP server to a URL like: jina-mcp-server.<your-account>.workers.dev/sse