Real-time search with content extraction, citations, and web crawling
The Tavily MCP Server provides real-time web search with content extraction, citations, and web crawling capabilities. Tavily is purpose-built for AI agents, returning clean, structured search results with source citations.
Built by Tavily AI, this server delivers search results optimized for LLM consumption. It supports search with automatic content extraction, domain filtering, and the ability to crawl specific URLs for deep content retrieval.
Designed for AI workflows that need reliable, up-to-date web information with proper source attribution and clean content formatting.
Add this to your MCP configuration file:
{
"mcpServers": {
"tavily": {
"args": [
"-y",
"tavily-mcp"
],
"command": "npx"
}
}
}Well-structured MCP server for Tavily's web search API with proper authentication handling and good security practices. The server appropriately requires an API key, implements proper error handling, and uses secure credential management through environment variables. Supply chain analysis found 4 known vulnerabilities in dependencies (0 critical, 4 high severity).
3 files analyzed · 6 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Be the first to review this server!
by Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
by mcp-marketplace · Developer Tools
Create, build, and publish Python MCP servers to PyPI — conversationally.
by mcp-marketplace · Developer Tools
Scaffold, build, and publish TypeScript MCP servers to npm — conversationally
by Microsoft · Content & Media
Convert files (PDF, Word, Excel, images, audio) to Markdown for LLM consumption
by mcp-marketplace · Finance
Free stock data and market news for any MCP-compatible AI assistant.
by xt765 · Developer Tools
Convert PDF, DOCX, HTML, Markdown, and Text for AI assistant context injection.