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Jina Web Search MCP

by hypersniper05
GitHub
Python
MIT License
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Jina Web Search MCP

Docker Python MCP License GitHub Stars

A Model Context Protocol (MCP) server that provides tools for fetching URL content and performing web searches using the Jina AI API. Built with the official MCP Python SDK.

Framework: Model Context Protocol Python SDK by Anthropic

Features

  • MCP Protocol Compliance: Fully compliant with Model Context Protocol 2025-06-18

  • FastMCP Implementation: Built with the official Python MCP SDK

  • Docker Support: Easy deployment with Docker and Docker Compose

  • Streamable HTTP Transport: Runs on port 5003 with modern transport

  • Two Core Tools:

    • fetch_url_content: Fetch content from any URL using Jina AI crawler

    • web_search: Perform web searches with semantic understanding

  • Claude Desktop Integration: Easy installation with mcp install

  • Development Tools: Built-in testing with mcp dev

  • Error Handling: Graceful error responses for failed requests

  • Environment Configuration: Configurable API keys via environment variables

  • Cross-Platform: Works on Windows, Linux, and macOS

  • Comprehensive Logging: Debug and monitor with detailed logs

Prerequisites

  • Python 3.8+ (required for MCP)

  • Docker & Docker Compose (recommended for deployment) OR

  • uv (recommended) or pip for package management

  • Jina AI API Key (Get one here)

API Key Setup

Important: You need a Jina AI API key to use this server.

  1. Get your API key from Jina AI

  2. Create a .env file:

    cp .env.example .env # Edit .env and add: JINA_API_KEY=your_actual_api_key_here

Installation Options

Option 1: Claude Desktop Integration (Easiest)

Install directly into Claude Desktop for immediate use:

# Clone the repository git clone https://github.com/hypersniper05/JinaWebSearchMCP.git cd JinaWebSearchMCP # Set your API key export JINA_API_KEY=your_actual_api_key_here # Linux/Mac # OR set JINA_API_KEY=your_actual_api_key_here # Windows # Install dependencies and add to Claude Desktop pip install -r requirements.txt mcp install server.py --name "Jina Web Search"

Option 2: Development & Testing

Test and debug your server with the MCP Inspector:

# Install dependencies (using uv - recommended) uv add mcp[cli] requests # Test with MCP development tools uv run mcp dev server.py # Or using pip pip install -r requirements.txt mcp dev server.py

Option 3: Docker (Production)

# Clone the repository git clone https://github.com/hypersniper05/JinaWebSearchMCP.git cd JinaWebSearchMCP # Set your API key in .env file cp .env.example .env # Edit .env and set your JINA_API_KEY # Build and run with Docker Compose docker-compose up -d # Check logs docker-compose logs -f # Stop the server docker-compose down

Easy startup scripts:

  • Windows: run.bat or run.ps1

  • Linux/Mac: ./run.sh (make executable with chmod +x run.sh)

Option 4: Direct Execution

# Install dependencies pip install -r requirements.txt # Set environment variable export JINA_API_KEY=your_api_key_here # Linux/Mac # OR set JINA_API_KEY=your_api_key_here # Windows # Run the server directly python server.py

The server will be available at http://localhost:5003

Configuration

Environment Variables

Variable

Description

Required

Default

JINA_API_KEY

Your Jina AI API key

Yes

your_jina_api_key_here

Server Configuration

  • Host: 0.0.0.0 (all interfaces for Docker compatibility)

  • Port: 5003

  • Transport: Streamable HTTP (modern MCP transport)

  • Protocol: Model Context Protocol 2025-06-18

  • Framework: FastMCP (official Python SDK)

Available Tools

fetch_url_content

Fetches and returns content from a given URL using Jina AI's crawler service.

Parameters:

  • url (string): The URL to fetch content from

Example Usage:

{ "name": "fetch_url_content", "arguments": { "url": "https://example.com" } }

web_search

Performs a semantic web search using Jina AI API.

Parameters:

  • query (string): Search query to execute

Example Usage:

{ "name": "web_search", "arguments": { "query": "latest technology news" } }

MCP Integration

Claude Desktop

Once installed, your server appears in Claude Desktop:

  1. Install: mcp install server.py --name "Jina Web Search"

  2. Available tools will appear in Claude's interface

  3. Use naturally: Ask Claude to search the web or fetch URL content

  4. Logs: Check ~/.config/claude-desktop/ for logs

Other MCP Clients

This server works with any MCP-compatible client:

  • VS Code MCP Extension: Connect via streamable HTTP

  • Custom clients: Use the official MCP Python SDK

  • Browser clients: Connect to http://localhost:5003/mcp

Client Example:

{ "mcpServers": { "websearch": { "url": "http://localhost:5003/mcp" } } }

Docker Details

The Docker setup includes:

  • Multi-stage build optimization for smaller images

  • Health checks for container monitoring

  • Environment variable handling for secure API key management

  • Automatic restart policies for production reliability

  • Port mapping for easy access (5003:5003)

Contributing

  1. Fork the repository

  2. Create a feature branch (git checkout -b feature/amazing-feature)

  3. Make your changes

  4. Commit your changes (git commit -m 'Add some amazing feature')

  5. Push to the branch (git push origin feature/amazing-feature)

  6. Open a Pull Request

License

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

Acknowledgments

Support

Built with ❀️ using the

This server cannot be installed

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

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables web content retrieval and semantic search capabilities through the Jina AI API. Provides tools to fetch content from URLs and perform intelligent web searches with natural language queries.

  1. Features
    1. Prerequisites
      1. API Key Setup
        1. Installation Options
          1. Option 1: Claude Desktop Integration (Easiest)
          2. Option 2: Development & Testing
          3. Option 3: Docker (Production)
          4. Option 4: Direct Execution
        2. Configuration
          1. Environment Variables
          2. Server Configuration
        3. Available Tools
          1. fetch_url_content
          2. web_search
        4. MCP Integration
          1. Claude Desktop
          2. Other MCP Clients
        5. Docker Details
          1. Contributing
            1. License
              1. Acknowledgments
                1. Support

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