Create powerful collaborative AI workflows by connecting multiple MCP servers including Jira, Google Calendar, Supabase for enhanced multi-agent automation capabilities in Klavis AI.
Jira is a project management and issue tracking tool developed by Atlassian
Google Calendar is a time-management and scheduling calendar service
Supabase official MCP Server
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"))
jira_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.JIRA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
google_calendar_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_CALENDAR,
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,
)
# Initialize MCP tools for each server
jira_tools = MCPServerAdapter(jira_mcp_instance.server_params)
google_calendar_tools = MCPServerAdapter(google_calendar_mcp_instance.server_params)
supabase_tools = MCPServerAdapter(supabase_mcp_instance.server_params)
# Create specialized agents for each service
jira_agent = Agent(
role="Jira Specialist",
goal="Handle all Jira related tasks and data processing",
backstory="You are an expert in Jira operations and data analysis",
tools=jira_tools,
reasoning=True,
verbose=False
)
google_calendar_agent = Agent(
role="Google Calendar Specialist",
goal="Handle all Google Calendar related tasks and data processing",
backstory="You are an expert in Google Calendar operations and data analysis",
tools=google_calendar_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
)
# 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=jira_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=google_calendar_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[jira_agent, google_calendar_agent, supabase_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()
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