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Ddg Server

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A web-based search interface using DuckDuckGo's search API, built with Python and Gradio, providing real-time search results and optional AI-powered summarizati

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About

A web-based search interface using DuckDuckGo's search API, built with Python and Gradio, providing real-time search results and optional AI-powered summarization.

README

A web-based search interface using DuckDuckGo's search API, built with Python and Gradio.

Docker Setup

Prerequisites

  • Docker installed on your system
  • Git (optional, for cloning the repository)

Building the Docker Image

  1. Clone the repository (if you haven't already):
git clone <repository-url>
cd ddg_mcp_server
  1. Build the Docker image:
docker build -t ddg-mcp-server .

Running the Container

Run the container with port 7860 mapped to your host:

docker run -p 7860:7860 ddg-mcp-server

The application will be available at:

Troubleshooting

If you cannot connect to the application:

  1. Verify the container is running:
docker ps
  1. Check the container logs:
docker logs $(docker ps -q)
  1. Try stopping any existing containers and starting fresh:
docker stop $(docker ps -q)
docker run -p 7860:7860 ddg-mcp-server

Features

  • Web-based search interface using DuckDuckGo
  • Real-time search results with full content
  • Markdown-formatted output
  • Configurable number of results
  • AI-powered content summarization (see SUMMARIZATION.md for details)

Development

The application is built with:

  • Python 3.10
  • Gradio for the web interface
  • DuckDuckGo Search API
  • BeautifulSoup4 for web scraping
  • Markdownify for content conversion

API Configuration for Summarization

This application supports content summarization using OpenAI's API or any compatible API service. To enable this feature:

  1. Copy the .env.example file to .env:
cp .env.example .env
  1. Edit the .env file and set your API credentials:
OPENAI_API_URL=https://api.openai.com/v1
ACCESS_TOKEN=your_api_key_here

Notes:

  • OPENAI_API_URL defaults to the official OpenAI API server if not specified
  • ACCESS_TOKEN is required for the summarization feature to work
  • You can use any OpenAI-compatible API by changing the OPENAI_API_URL

Running with Docker and API Credentials

To run the Docker container with your API credentials:

docker run -p 7860:7860 \
  -e OPENAI_API_URL="https://api.openai.com/v1" \
  -e ACCESS_TOKEN="your_api_key_here" \
  ddg-mcp-server

Testing the API Connection

After configuring your API credentials, you can test if the connection works correctly:

python main.py --test-api

This will validate your API credentials without starting the full server.

Model Configuration

The AI model used for summarization can be configured in the config.py file:

# Default model to use for summarization
DEFAULT_MODEL = "gpt-4.1-turbo"

For detailed instructions on model configuration, see SUMMARIZATION.md.

from github.com/shgsousa/ddg_mcp_server

Install Ddg Server in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install ddg-mcp-server

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add ddg-mcp-server -- uvx ddg-mcp-server

FAQ

Is Ddg Server MCP free?

Yes, Ddg Server MCP is free — one-click install via Unyly at no cost.

Does Ddg Server need an API key?

No, Ddg Server runs without API keys or environment variables.

Is Ddg Server hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Ddg Server in Claude Desktop, Claude Code or Cursor?

Open Ddg Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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