Web-Scout: AI-Powered Search with LLM Summarization

A FastAPI application that performs web searches using DuckDuckGo and generates AI-powered summaries using Google's Gemini AI.

Features

• Web search using DuckDuckGo

• AI summarization using Gemini 2.5 Flash

• Two output modes: Summary and Detailed analysis

• Docker & Docker Compose ready

• Secure API key management via environment variables

• MCP (Model Context Protocol) support over HTTP

Prerequisites

• Docker and Docker Compose installed

• Google Gemini API key

Setup

1. Clone the repository (or navigate to your project directory)

2. Add your Gemini API key to the .env file:

   GEMINI_API_KEY=your_actual_gemini_api_key_here

3. Build and run with Docker Compose:

   docker-compose up --build

API Usage

The application will be available at http://localhost:8000

Health Check

Search Endpoint

Summary Mode (Default)

Detailed Mode

Response Format

MCP Server Integration

Web-Scout can also function as an MCP (Model Context Protocol) server, allowing AI assistants to perform web searches directly through tools.

MCP Features

• Web Search Tool: Perform web searches with AI summarization

• Dual Mode Support: Both summary and detailed analysis modes

• HTTP Transport: MCP over HTTP protocol for client integration

• JSON Responses: Structured output for easy integration

MCP Tools Available

Web Search Tool

• Name: web_search

• Description: Perform a web search using DuckDuckGo and generate AI-powered summaries

• Parameters:

  • query (string, required): The search query to perform

  • mode (string, optional): Response mode - "summary" or "detailed" (default: "summary")

MCP Server Setup

Web-Scout provides MCP functionality over HTTP, accessible at the /mcp endpoint.

Method 1: Direct FastAPI Server

1. Install dependencies:

2. Set your Gemini API key:

3. Run the HTTP server with MCP endpoint:

The MCP endpoint will be available at http://localhost:8000/mcp

Method 2: Docker Container

Or run standalone container

docker run -p 8000:8000 -e GEMINI_API_KEY=your_api_key_here web-scout

Integrating with AI Tools

To use Web-Scout as an MCP server with AI tools like Claude Desktop or Roo:

1. Create MCP Configuration:

2. Configure your AI tool to use the MCP configuration:

   • For Claude Desktop: Add to ~/Library/Application Support/Claude/claude_desktop_config.json

   • For Roo: Add to the appropriate configuration file

3. Usage Example:

The AI tool will use the Web-Scout MCP server (via the /mcp endpoint) to perform the search and provide summarized results.

Development

Local Development (without Docker)

Using Docker Compose

Configuration

Environment Variables

• GEMINI_API_KEY: Your Google Gemini API key (required)

Docker Configuration

• Port: 8000

• Container name: web-scout

• Health check: Automatic health monitoring

Security Notes

• The .env file is ignored by Git and should never be committed

• API keys are mounted securely via Docker Compose volumes

• The application uses health checks for monitoring

Error Handling

• Returns proper HTTP status codes

• Includes detailed error messages

• Handles missing API keys and invalid parameters gracefully