Connectto Asana, Attio, WhatsApp MCP Servers
Create powerful collaborative AI workflows by connecting multiple MCP servers including Asana, Attio, WhatsApp for enhanced multi-agent automation capabilities in Klavis AI.
Asana
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
Available Tools:
- asana_create_task
- asana_get_task
- asana_search_tasks
- +16 more tools
Attio
Attio is a next-generation CRM platform that helps teams build stronger relationships with their customers through powerful data management and automation
Available Tools:
- attio_search_people
- attio_search_companies
- attio_search_deals
- +2 more tools
WhatsApp Business API integration that enables sending text messages, media, and managing conversations with customers. Perfect for customer support, marketing campaigns, and automated messaging workflows through the official WhatsApp Business platform.
Available Tools:
- whatsapp_send_text
Quick Setup Guide
Follow these steps to connect CrewAI to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Agents & Tools
Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.
Deploy Your Crew
Test your multi-agent workflows and start using your enhanced collaborative AI capabilities.
CrewAI + KlavisAI Integration Snippets
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,
)
attio_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.ATTIO,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
whatsapp_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.WHATSAPP,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
asana_tools = MCPServerAdapter(asana_mcp_instance.server_params)
attio_tools = MCPServerAdapter(attio_mcp_instance.server_params)
whatsapp_tools = MCPServerAdapter(whatsapp_mcp_instance.server_params)
# Create specialized agents for each service
asana_agent = Agent(
role="Asana Specialist",
goal="Handle all Asana related tasks and data processing",
backstory="You are an expert in Asana operations and data analysis",
tools=asana_tools,
reasoning=True,
verbose=False
)
attio_agent = Agent(
role="Attio Specialist",
goal="Handle all Attio related tasks and data processing",
backstory="You are an expert in Attio operations and data analysis",
tools=attio_tools,
reasoning=True,
verbose=False
)
whatsapp_agent = Agent(
role="WhatsApp Specialist",
goal="Handle all WhatsApp related tasks and data processing",
backstory="You are an expert in WhatsApp operations and data analysis",
tools=whatsapp_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=asana_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=attio_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[asana_agent, attio_agent, whatsapp_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()Frequently Asked Questions
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