Connectto Tavily MCP Server
Seamlessly integrate your Google Gemini applications with Tavily using Klavis AI's comprehensive MCP server connection guide.
Tavily
Tavily is an AI-powered search API designed for LLMs and AI agents. Get real-time web search results, extract content from URLs, crawl websites, and generate site maps with advanced filtering and parsing capabilities
Available Tools:
- tavily_search
- tavily_extract
- tavily_crawl
- +1 more tools
Quick Setup Guide
Follow these steps to connect Google Gemini to this MCP server
Create Your Account
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Configure Connections
Add the MCP server to Gemini and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
Google Gemini + KlavisAI Integration Snippets
import os
from google import genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
client = genai.Client(api_key=os.getenv("GOOGLE_API_KEY"))
user_message = "Your query here"
tavily_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.TAVILY,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
mcp_tools = klavis_client.mcp_server.list_tools(
server_url=tavily_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
response = client.models.generate_content(
model="gemini-2.5-flash",
contents=user_message,
config=genai.types.GenerateContentConfig(
tools=mcp_tools.tools,
),
)Frequently Asked Questions
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