Create powerful AI workflows by connecting multiple MCP servers including Mixpanel, ClickUp, Google Docs for enhanced automation capabilities in Klavis AI.
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
ClickUp is a comprehensive project management and productivity platform that helps teams organize tasks, manage projects, and collaborate effectively with customizable workflows and powerful tracking features
Google Docs is a word processor included as part of the free, web-based Google Docs Editors suite
Follow these steps to connect Together AI to these MCP servers
Sign up for KlavisAI to access our MCP server management platform.
Add your desired MCP servers to Together AI and configure authentication settings.
Verify your connections work correctly and start using your enhanced AI capabilities.
import os
import json
from together import Together
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
together_client = Together(api_key=os.getenv("TOGETHER_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
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,
)
clickup_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CLICKUP,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
google_docs_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_DOCS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get all MCP tools
mixpanel_tools = klavis_client.mcp_server.list_tools(
server_url=mixpanel_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
clickup_tools = klavis_client.mcp_server.list_tools(
server_url=clickup_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
google_docs_tools = klavis_client.mcp_server.list_tools(
server_url=google_docs_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(mixpanel_tools.tools)
all_tools.extend(clickup_tools.tools)
all_tools.extend(google_docs_tools.tools)
messages = [
{"role": "system", "content": "You are a helpful AI assistant with access to multiple data sources."},
{"role": "user", "content": user_message}
]
response = together_client.chat.completions.create(
model="meta-llama/Llama-2-70b-chat-hf",
messages=messages,
tools=all_tools
)
Everything you need to know about connecting to these MCP servers
Join developers who are already using KlavisAI to power their Together AI applications with these MCP servers.
Start For Free