What is Ddg Mcp Server

ddg_mcp_server is a web search tool and API that utilizes DuckDuckGo’s search capabilities, Gradio for the web interface, and MCP for integration. It provides a user-friendly interface to fetch web search results, extract summaries, and retrieve full content in markdown format.

Use cases

Use cases for ddg_mcp_server include building search functionalities for applications, automating content retrieval for research, creating tools for summarizing web content, and integrating search features into desktop applications.

How to use

To use ddg_mcp_server, you need to have Docker installed. Clone the repository, build the Docker image, and run the container with port 7860 mapped to your host. Access the application via http://localhost:7860.

Key features

Key features include a web-based search interface using DuckDuckGo, real-time search results with full content retrieval, markdown-formatted output, and a configurable number of results.

Where to use

ddg_mcp_server can be used in various fields such as web development, data analysis, content creation, and any application that requires web search capabilities.

DuckDuckGo MCP Server

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

2. 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:

• http://localhost:7860
• http://127.0.0.1:7860

Troubleshooting

If you cannot connect to the application:

1. Verify the container is running:

docker ps

2. Check the container logs:

docker logs $(docker ps -q)

3. 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

2. 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.