ConnectCrewAIto Perplexity, Klavis ReportGen, Motion 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"))

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

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

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

# Initialize MCP tools for each server
perplexity_tools = MCPServerAdapter(perplexity_mcp_instance.server_params)
klavis_reportgen_tools = MCPServerAdapter(klavis_reportgen_mcp_instance.server_params)
motion_tools = MCPServerAdapter(motion_mcp_instance.server_params)

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

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

motion_agent = Agent(
    role="Motion Specialist",
    goal="Handle all Motion related tasks and data processing",
    backstory="You are an expert in Motion operations and data analysis",
    tools=motion_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=perplexity_agent,
    markdown=True
)

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

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

result = multi_agent_crew.kickoff()