ConnectCrewAIto Slack, Exa, Mem0 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"))

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

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

mem0_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MEM0,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Initialize MCP tools for each server
slack_tools = MCPServerAdapter(slack_mcp_instance.server_params)
exa_tools = MCPServerAdapter(exa_mcp_instance.server_params)
mem0_tools = MCPServerAdapter(mem0_mcp_instance.server_params)

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

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

mem0_agent = Agent(
    role="Mem0 Specialist",
    goal="Handle all Mem0 related tasks and data processing",
    backstory="You are an expert in Mem0 operations and data analysis",
    tools=mem0_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=slack_agent,
    markdown=True
)

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

# Create multi-agent crew
multi_agent_crew = Crew(
    agents=[slack_agent, exa_agent, mem0_agent],
    tasks=[research_task, analysis_task],
    verbose=False,
    process=Process.sequential
)

result = multi_agent_crew.kickoff()