DuckDuckGo Search
This DuckDuckGo search implementation for the Model Context Protocol (MCP), developed by qwang07, enables AI models to perform web searches using the DuckDuckGo engine. Built with TypeScript and leveraging the duck-duck-scrape library, it provides a simple interface for querying DuckDuckGo and retrieving search results. The implementation stands out by offering easy integration with MCP-compatible AI systems and respecting DuckDuckGo's privacy-focused approach. It's particularly useful for AI assistants or applications needing up-to-date web information, enabling tasks like fact-checking, research, or providing current event updates without relying on potentially outdated training data.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- browser-automation
- Source
- PulseMCP
- Repository
- github.com/qwang07/duck-duck-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve DuckDuckGo Search from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp --scope user for --scope project to commit it to .mcp.json.