Seamlessly integrate your CrewAI multi-agent systems with Asana using Klavis AI's comprehensive MCP server connection guide.
Asana is a web and mobile application designed to help teams organize, track, and manage their work. It provides project management tools, task assignment, collaboration features, and progress tracking to boost team productivity
Follow these steps to connect CrewAI to this MCP server
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Set up your CrewAI agents with the MCP server tools and configure authentication settings for collaborative workflows.
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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"))
asana_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.ASANA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
with MCPServerAdapter(asana_mcp_instance.server_params) as mcp_tools:
# Create a Asana Analysis Agent
asana_agent = Agent(
role="Asana Analyst",
goal="Research and analyze asana to extract comprehensive insights",
backstory="You are an expert at analyzing asana and creating professional summaries.",
tools=mcp_tools,
reasoning=True,
verbose=False
)
# Define Task
analysis_task = Task(
description=f"Research and analyze asana 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=asana_agent,
markdown=True
)
# Create and execute the crew
asana_crew = Crew(
agents=[asana_agent],
tasks=[analysis_task],
verbose=False,
process=Process.sequential
)
result = asana_crew.kickoff()
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