Create powerful collaborative AI workflows by connecting multiple MCP servers including PostHog, ServiceNow for enhanced multi-agent automation capabilities in Klavis AI.
PostHog is an open-source product analytics platform. Track events, analyze user behavior, run experiments, manage feature flags, and generate insights via OpenAPI integration
ServiceNow is a cloud-based software platform that helps companies manage and automate digital workflows for their enterprise operations, particularly in IT, human resources, and customer service.
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"))
posthog_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.POSTHOG,
user_id="1234",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
servicenow_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.SERVICENOW,
user_id="1234",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
posthog_tools = MCPServerAdapter(posthog_mcp_instance.server_params)
servicenow_tools = MCPServerAdapter(servicenow_mcp_instance.server_params)
# Create specialized agents for each service
posthog_agent = Agent(
role="PostHog Specialist",
goal="Handle all PostHog related tasks and data processing",
backstory="You are an expert in PostHog operations and data analysis",
tools=posthog_tools,
reasoning=True,
verbose=False
)
servicenow_agent = Agent(
role="ServiceNow Specialist",
goal="Handle all ServiceNow related tasks and data processing",
backstory="You are an expert in ServiceNow operations and data analysis",
tools=servicenow_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=posthog_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=servicenow_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[posthog_agent, servicenow_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()
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