search
Pack: tavily · Endpoint: https://gateway.pipeworx.io/tavily/mcp
AI/LLM-optimized web search built for RAG: returns a synthesized natural-language answer plus a ranked list of sourced results (title, url, content snippet, relevance score). Prefer this over scraping a generic search engine when you need grounded, citable web context. Example: search({ query: “latest SpaceX Starship test result” })
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
query | string | yes | The search query / question to research. |
search_depth | string | no | Search depth: “basic” (fast, default) or “advanced” (deeper, more thorough). |
max_results | number | no | Maximum number of results to return (default 5, max 20). |
topic | string | no | Search topic: “general” (default) or “news” for recent news coverage. |
include_answer | boolean | no | Whether to include a synthesized AI answer string (default true). |
_apiKey | string | no | Optional — your own Tavily API key for higher limits; omit to use the shared Pipeworx key. |
Example call
curl -X POST https://gateway.pipeworx.io/tavily/mcp \
-H 'Content-Type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{}}}'Connect
Add this to your MCP client config, or use one-click install buttons:
{
"mcpServers": {
"tavily": {
"url": "https://gateway.pipeworx.io/tavily/mcp"
}
}
}See Getting Started for client-specific install steps.