F
licenseC
qualityD
maintenanceEnables web search capabilities through the Tavily API via the Model Context Protocol. Allows users to perform web searches and retrieve information from the internet through natural language queries.
5
-
MCP DuckDuckGo Search
by shaheen2013
Provides tools to query the DuckDuckGo Instant Answer API for search results.
Click on "Deploy 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., "@MCP DuckDuckGo Searchwhat is the population of Tokyo?"
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.
MCP DuckDuckGo Search
A Model Context Protocol (MCP) server querying DuckDuckGo Instant Answer API.
Installation
Installing via Smithery
To install DuckDuckGo Search for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @shaheen2013/duckduckgo-search-mcp-server --client claudeManual Installation
# Clone the repository
git clone https://github.com/shaheen2013/duckduckgo-search-mcp-server.git
cd duckduckgo-search-mcp-server
# Install dependencies
npm install
# Build the project
npm run buildDocker
You can test this MCP server using Docker. To do this first run:
docker build -t duckduckgo-search-mcp-server .
docker run -p 8080:8080 duckduckgo-search-mcp-serverYou can then test the server running within Docker via the inspector e.g.
pnpm run inspector http://localhost:8080Related MCP server: Google Search MCP Server
Usage
Running the Server
You can use the MCP Inspector to test the server:
npm run inspectorAccess the MCP Inspector and then test the tool e.g.
Development
Project Structure
src/index.ts- Main server implementation
Available Scripts
npm run build- Build the TypeScript codenpm run watch- Watch for changes and rebuildnpm run inspector- Run the MCP Inspector against the server
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Acknowledgments
Available Tools
1 toolduckduckgo_searchC
Search DuckDuckGo Instant Answer API for a query string
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
TDQS
C2.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits beyond the obvious. For example, it doesn't mention if the search is read-only, rate limits, or result format, which is necessary for an API call.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no filler. However, it is overly brief and could include more detail without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema and siblings, the description is minimally adequate. However, it lacks information about response structure or any caveats, which would complete the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'query' has no description in the schema (0% coverage), and the description does not add any meaning, format instructions, or examples beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches the DuckDuckGo Instant Answer API for a query string, specifying the verb and resource. However, 'Instant Answer API' is a specific term that might not be universally understood, slightly reducing clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool, prerequisites, or alternatives. It simply states the function without context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.0- First observed
duckduckgo_search
TDQS
B3.1/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no possibility for confusion or overlap. The single tool is clearly distinct by default.
Naming Consistency5/5
The naming is perfectly consistent as there is only one tool. The verb_noun pattern is clear and appropriate.
Tool Count3/5
A single tool for a search service is minimal. It may be sufficient for simple queries, but the tool count feels thin for a typical API surface.
Completeness2/5
The tool only performs a simple search. There are no supporting tools for pagination, fetching detailed results, or handling errors, making the surface incomplete for advanced use cases.
Maintenance
ActivityInactive
ResponsivenessNo issues
Related MCP Connectors
LLM-ready web search + instant answers + URL-to-clean-text fetch for agents and RAG.
Provides AI assistants with access to Seltz's powerful Web Search capabilities.
Web search, scraping, Google Trends and data lookups. Paid per call in USDC on Base via x402.
Search @imqueue docs and scaffold typed services & clients from your AI coding agent.
Related MCP Servers
- AlicenseAqualityDmaintenanceEnables users to perform Google Custom Search queries through the Model Context Protocol. Requires Google API credentials and Custom Search Engine configuration for web search functionality.1MIT
- FlicenseNot gradedqualityDmaintenanceEnables web search capabilities using DuckDuckGo's free API without requiring authentication or API keys.-
- FlicenseCqualityDmaintenanceEnables web search capabilities through the Tavily API, allowing users to search the web for information using natural language queries through the Model Context Protocol.21-