tavily-mcp-python

tavily-mcp-python

Tavily MCP Server implementation that uses fastmcp and supports both sse and stdio transports. It also supports more up to date functionalities of Tavily.

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Tools

tavily-search

A powerful web search tool that provides comprehensive, real-time results using Tavily's AI search engine. Returns relevant web content with customizable parameters for result count, content type, and domain filtering. Ideal for gathering current information, news, and detailed web content analysis.

tavily-extract

A powerful web content extraction tool that retrieves and processes raw content from specified URLs, ideal for data collection, content analysis, and research tasks.

tavily-crawl

A powerful web crawler that initiates a structured web crawl starting from a specified base URL. The crawler expands from that point like a tree, following internal links across pages. You can control how deep and wide it goes, and guide it to focus on specific sections of the site.

tavily-map

A powerful web mapping tool that creates a structured map of website URLs, allowing you to discover and analyze site structure, content organization, and navigation paths. Perfect for site audits, content discovery, and understanding website architecture.

README

Tavily MCP Server

Tavily MCP Server implementation that uses fastmcp and supports both sse and stdio transports. To use this server, you need a Tavily account and a Tavily API key, which must be loaded into the TAVILY_API_KEY environment variable.

The Tavily MCP server provides:

  • search, extract, map, crawl tools
  • Real-time web search capabilities through the tavily-search tool
  • Intelligent data extraction from web pages via the tavily-extract tool
  • Powerful web mapping tool that creates a structured map of website
  • Web crawler that systematically explores websites

Prerequisites

  • git installed. (To clone the repo)
  • uv installed.
  • docker installed (Optional: If you are planning to use the SSE server inside a docker container).

To install uv in Linux and MacOS type this in your terminal:

curl -LsSf https://astral.sh/uv/install.sh | sh

Environment Variables

Copy the .env.example file and rename that to .env. Then paste your TAVILY_API_KEY inside there

TAVILY_API_KEY=<YOUR-API-KEY>

Optional: You can also configure the port if you are planning to use SSE.

TAVILY_MCP_PORT=<PORT>

Running the SSE server

While inside the repo run:

uv run --env-file .env tavily-mcp-sse

Running on STDIO

{
  "mcpServers": {
    "tavily-mcp-server": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "<LOCATION-TO-THE-REPO>",
        "tavily-mcp-stdio"
      ],
      "env": {
        "TAVILY_API_KEY": "<YOUR-API-KEY>"
      }
    }
  }
}

Docker SSE Server

First you need to build the image using the Dockerfile inside this repository. Run this to build the image:

docker build -t tavily-mcp .

Then you can run the container using the environment variables inside the env file

docker run --name tavily-mcp \
  -p 127.0.0.1:8000:8000 \
  --env-file .env \
  tavily-mcp

Or you can specify the environment variables yourself.

docker run --name tavily-mcp \
  -p 127.0.0.1:8000:8000 \
  -e TAVILY_API_KEY=<YOUR-API-KEY>
  tavily-mcp

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