ddg_mcp_server
Provides web search capabilities using DuckDuckGo's search API, returning search results with content and markdown formatting.
Enables AI-powered content summarization of search results using OpenAI's API.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ddg_mcp_serversearch for latest news on artificial intelligence"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Clone the repository (if you haven't already):
git clone <repository-url>
cd ddg_mcp_serverBuild 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-serverThe application will be available at:
Troubleshooting
If you cannot connect to the application:
Verify the container is running:
docker psCheck the container logs:
docker logs $(docker ps -q)Try stopping any existing containers and starting fresh:
docker stop $(docker ps -q)
docker run -p 7860:7860 ddg-mcp-serverFeatures
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:
Copy the
.env.examplefile to.env:
cp .env.example .envEdit the
.envfile and set your API credentials:
OPENAI_API_URL=https://api.openai.com/v1
ACCESS_TOKEN=your_api_key_hereNotes:
OPENAI_API_URLdefaults to the official OpenAI API server if not specifiedACCESS_TOKENis required for the summarization feature to workYou 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-serverTesting the API Connection
After configuring your API credentials, you can test if the connection works correctly:
python main.py --test-apiThis 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.
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