ConnectCrewAIto Mixpanel, Moneybird, Attio MCP Servers

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"))

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,
)

moneybird_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MONEYBIRD,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

attio_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.ATTIO,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Initialize MCP tools for each server
mixpanel_tools = MCPServerAdapter(mixpanel_mcp_instance.server_params)
moneybird_tools = MCPServerAdapter(moneybird_mcp_instance.server_params)
attio_tools = MCPServerAdapter(attio_mcp_instance.server_params)

# Create specialized agents for each service
mixpanel_agent = Agent(
    role="Mixpanel Specialist",
    goal="Handle all Mixpanel related tasks and data processing",
    backstory="You are an expert in Mixpanel operations and data analysis",
    tools=mixpanel_tools,
    reasoning=True,
    verbose=False
)

moneybird_agent = Agent(
    role="Moneybird Specialist",
    goal="Handle all Moneybird related tasks and data processing",
    backstory="You are an expert in Moneybird operations and data analysis",
    tools=moneybird_tools,
    reasoning=True,
    verbose=False
)

attio_agent = Agent(
    role="Attio Specialist",
    goal="Handle all Attio related tasks and data processing",
    backstory="You are an expert in Attio operations and data analysis",
    tools=attio_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=mixpanel_agent,
    markdown=True
)

analysis_task = Task(
    description="Analyze and synthesize the gathered data",
    expected_output="Comprehensive analysis with insights and recommendations",
    agent=moneybird_agent,
    markdown=True
)

# Create multi-agent crew
multi_agent_crew = Crew(
    agents=[mixpanel_agent, moneybird_agent, attio_agent],
    tasks=[research_task, analysis_task],
    verbose=False,
    process=Process.sequential
)

result = multi_agent_crew.kickoff()