ConnectCrewAIto Markdown2doc, Klaviyo 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"))

markdown2doc_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MARKDOWN2DOC,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

klaviyo_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.KLAVIYO,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Initialize MCP tools for each server
markdown2doc_tools = MCPServerAdapter(markdown2doc_mcp_instance.server_params)
klaviyo_tools = MCPServerAdapter(klaviyo_mcp_instance.server_params)

# Create specialized agents for each service
markdown2doc_agent = Agent(
    role="Markdown2doc Specialist",
    goal="Handle all Markdown2doc related tasks and data processing",
    backstory="You are an expert in Markdown2doc operations and data analysis",
    tools=markdown2doc_tools,
    reasoning=True,
    verbose=False
)

klaviyo_agent = Agent(
    role="Klaviyo Specialist",
    goal="Handle all Klaviyo related tasks and data processing",
    backstory="You are an expert in Klaviyo operations and data analysis",
    tools=klaviyo_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=markdown2doc_agent,
    markdown=True
)

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

# Create multi-agent crew
multi_agent_crew = Crew(
    agents=[markdown2doc_agent, klaviyo_agent],
    tasks=[research_task, analysis_task],
    verbose=False,
    process=Process.sequential
)

result = multi_agent_crew.kickoff()