Create powerful collaborative AI workflows by connecting multiple MCP servers including Gmail, Supabase, Monday for enhanced multi-agent automation capabilities in Klavis AI.
Gmail is a free email service provided by Google
Supabase official MCP Server
Monday.com is a work operating system that powers teams to run projects and workflows with confidence. Create boards, manage items, customize columns, organize groups, and collaborate with team members in a visual workspace
Follow these steps to connect CrewAI to these MCP servers
Sign up for KlavisAI to access our MCP server management platform.
Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.
Test your multi-agent workflows and start using your enhanced collaborative AI capabilities.
import os
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
gmail_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GMAIL,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
supabase_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.SUPABASE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
monday_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.MONDAY,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
gmail_tools = MCPServerAdapter(gmail_mcp_instance.server_params)
supabase_tools = MCPServerAdapter(supabase_mcp_instance.server_params)
monday_tools = MCPServerAdapter(monday_mcp_instance.server_params)
# Create specialized agents for each service
gmail_agent = Agent(
role="Gmail Specialist",
goal="Handle all Gmail related tasks and data processing",
backstory="You are an expert in Gmail operations and data analysis",
tools=gmail_tools,
reasoning=True,
verbose=False
)
supabase_agent = Agent(
role="Supabase Specialist",
goal="Handle all Supabase related tasks and data processing",
backstory="You are an expert in Supabase operations and data analysis",
tools=supabase_tools,
reasoning=True,
verbose=False
)
monday_agent = Agent(
role="Monday Specialist",
goal="Handle all Monday related tasks and data processing",
backstory="You are an expert in Monday operations and data analysis",
tools=monday_tools,
reasoning=True,
verbose=False
)
# Define collaborative tasks
research_task = Task(
description="Gather comprehensive data from all available sources",
expected_output="Raw data and initial findings from all services",
agent=gmail_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=supabase_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[gmail_agent, supabase_agent, monday_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()
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