Create powerful collaborative AI workflows by connecting multiple MCP servers including Jira, ClickUp, Gong for enhanced multi-agent automation capabilities in Klavis AI.
Jira is a project management and issue tracking tool developed by Atlassian
ClickUp is a comprehensive project management and productivity platform that helps teams organize tasks, manage projects, and collaborate effectively with customizable workflows and powerful tracking features
Gong is a revenue intelligence platform that captures and analyzes all revenue-related interactions to help sales teams close more deals. It provides conversation analytics, deal insights, and sales performance tracking through call recordings and transcripts
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"))
jira_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.JIRA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
clickup_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CLICKUP,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
gong_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GONG,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
jira_tools = MCPServerAdapter(jira_mcp_instance.server_params)
clickup_tools = MCPServerAdapter(clickup_mcp_instance.server_params)
gong_tools = MCPServerAdapter(gong_mcp_instance.server_params)
# Create specialized agents for each service
jira_agent = Agent(
role="Jira Specialist",
goal="Handle all Jira related tasks and data processing",
backstory="You are an expert in Jira operations and data analysis",
tools=jira_tools,
reasoning=True,
verbose=False
)
clickup_agent = Agent(
role="ClickUp Specialist",
goal="Handle all ClickUp related tasks and data processing",
backstory="You are an expert in ClickUp operations and data analysis",
tools=clickup_tools,
reasoning=True,
verbose=False
)
gong_agent = Agent(
role="Gong Specialist",
goal="Handle all Gong related tasks and data processing",
backstory="You are an expert in Gong operations and data analysis",
tools=gong_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=jira_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=clickup_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[jira_agent, clickup_agent, gong_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()
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