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MCP-Jina-AI MCP Server

Provides URL content extraction and conversion to LLM-friendly text for MCP workflows using Jina.ai reader service.

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "kealuya-mcp-jina-ai": {
      "command": "mcp-jina-ai",
      "args": []
    }
  }
}

MCP-Jina-AI is a lightweight MCP server that leverages Jina.ai’s reader service to turn web pages into clean, structured text that is friendly for large language models. It enables you to fetch content from a URL and automatically convert it into an MCP-friendly format inside your workflows.

How to use

You integrate MCP-Jina-AI into your MCP client setup and point it at the URL you want processed. When invoked through MCP, it will return the extracted content in a structured, LLM-friendly format that you can feed into your AI models or downstream processing steps.

How to install

Prerequisites you need before installation:

- Go is required on your system.

Install the MCP-Jina-AI tool directly with Go:

go install github.com/kealuya/mcp-jina-ai@latest

Ensure your GOPATH is set and included in your system PATH so the mcp-jina-ai binary is accessible from MCP.

Configure MCP to use the server by adding the following to your MCP configuration file. This enables MCP to recognize and start the mcp-jina-ai server.

{
  "mcpServers": {
    "mcp-jina-ai": {
      "command": "mcp-jina-ai"
    }
  }
}

Restart the MCP service to apply the new configuration and enable the mcp-jina-ai server for use within your MCP client.

Additional configuration and notes

Jina.ai’s reader service is referenced as a simple way to access page content. The approach uses a URL wrapper so you can fetch the main content of a page in a form suitable for LLMs.

Example concept: you pass a target URL to MCP-Jina-AI and receive a cleaned, structured text output optimized for large language models.

Examples and reference configurations

Configuration example for MCP to recognize this server is provided below. This is used to start and route requests through the mcp-jina-ai tool within your MCP setup.

Tools and endpoints overview

MCP-Jina-AI focuses on two core capabilities within MCP workflows: content extraction from URLs and formatting content for LLM consumption. The following tools summarize these capabilities.

Security and operations

Treat web content responsibly and respect the terms of service for any URL you fetch. Ensure your MCP environment protects any sensitive data that might be transmitted or stored during processing.

Available tools

extractContent

Extracts and retrieves the main text content from a given URL using Jina.ai reader service, returning clean, structured text suitable for LLM processing.

formatForLLM

Converts the raw extracted content into a structured, model-friendly format optimized for large language models, including sections, summaries, and logical organization.