Seamlessly integrate your CrewAI multi-agent systems with Jira using Klavis AI's comprehensive MCP server connection guide.
Jira is a project management and issue tracking tool developed by Atlassian
Follow these steps to connect CrewAI to this MCP server
Sign up for KlavisAI to access our MCP server management platform.
Set up your CrewAI agents with the MCP server 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,
)
with MCPServerAdapter(jira_mcp_instance.server_params) as mcp_tools:
# Create a Jira Analysis Agent
jira_agent = Agent(
role="Jira Analyst",
goal="Research and analyze jira to extract comprehensive insights",
backstory="You are an expert at analyzing jira and creating professional summaries.",
tools=mcp_tools,
reasoning=True,
verbose=False
)
# Define Task
analysis_task = Task(
description=f"Research and analyze jira data. Extract relevant information and create a comprehensive summary with key points and main takeaways.",
expected_output="Complete analysis with structured summary, key insights, and main takeaways",
agent=jira_agent,
markdown=True
)
# Create and execute the crew
jira_crew = Crew(
agents=[jira_agent],
tasks=[analysis_task],
verbose=False,
process=Process.sequential
)
result = jira_crew.kickoff()
Everything you need to know about connecting CrewAI to this MCP server
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