Connectto Mixpanel, Tavily, Google Jobs MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Mixpanel, Tavily, Google Jobs for enhanced automation capabilities in Klavis AI.
Mixpanel
Mixpanel is a powerful product analytics platform that helps teams understand user behavior, track events, analyze conversion funnels, measure retention, and make data-driven decisions with real-time insights and advanced segmentation capabilities
Available Tools:
- mixpanel_send_events
- mixpanel_get_events
- mixpanel_get_event_properties
- +6 more tools
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
Google Jobs
Google Jobs is a comprehensive job search platform that aggregates listings from across the web. Search for jobs by location, company, employment type, and more, with detailed information about requirements, benefits, and application processes
Available Tools:
- google_jobs_search
- google_jobs_get_details
- google_jobs_search_by_company
- +2 more tools
Quick Setup Guide
Follow these steps to connect OpenAI to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Connections
Add your desired MCP servers to OpenAI and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
OpenAI + KlavisAI Integration Snippets
import json
import os
from openai import OpenAI
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
# Constants
OPENAI_MODEL = "gpt-4o-mini"
mixpanel_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.MIXPANEL,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
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,
)
google_jobs_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_JOBS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get tools from all MCP servers
mixpanel_tools = klavis_client.mcp_server.list_tools(
server_url=mixpanel_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
tavily_tools = klavis_client.mcp_server.list_tools(
server_url=tavily_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
google_jobs_tools = klavis_client.mcp_server.list_tools(
server_url=google_jobs_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(mixpanel_tools)
all_tools.extend(tavily_tools)
all_tools.extend(google_jobs_tools)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": user_message}
]
response = openai_client.chat.completions.create(
model=OPENAI_MODEL,
messages=messages,
tools=all_tools if all_tools else None
)Frequently Asked Questions
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