DuckDuckGo MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| searchB | |
| fetch_contentC | |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: 'fetch_content' retrieves and parses content from a specific webpage URL, while 'search' queries DuckDuckGo for results. There is no overlap in functionality, and an agent can easily differentiate between fetching known content and searching for unknown information.
Both tool names follow a consistent verb-based pattern: 'fetch_content' and 'search'. They use snake_case uniformly, and the verbs ('fetch', 'search') are clear and appropriate for their actions, making the naming predictable and readable.
With only 2 tools, the server feels under-scoped for a DuckDuckGo MCP server. While the tools cover basic web content fetching and search, the domain suggests potential for more operations (e.g., image search, news search, or advanced query parameters), making the count too low for the apparent scope.
The tools cover core functionalities of fetching web content and searching, but there are notable gaps. For a DuckDuckGo server, missing operations like image search, video search, or localized searches could limit agent capabilities, though basic workflows are supported.