Create powerful collaborative AI workflows by connecting multiple MCP servers including WordPress, Outlook Mail, Airtable for enhanced multi-agent automation capabilities in Klavis AI.
WordPress is an open-source content management system for building websites and blogs
Outlook Mail is a web-based suite of webmail, contacts, tasks, and calendaring services from Microsoft
Airtable is a cloud-based database and spreadsheet platform that combines the flexibility of a spreadsheet with the power of a database, enabling teams to organize, track, and collaborate on projects with customizable views and powerful automation features
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"))
wordpress_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.WORDPRESS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
outlook_mail_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.OUTLOOK_MAIL,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
airtable_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.AIRTABLE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
wordpress_tools = MCPServerAdapter(wordpress_mcp_instance.server_params)
outlook_mail_tools = MCPServerAdapter(outlook_mail_mcp_instance.server_params)
airtable_tools = MCPServerAdapter(airtable_mcp_instance.server_params)
# Create specialized agents for each service
wordpress_agent = Agent(
role="WordPress Specialist",
goal="Handle all WordPress related tasks and data processing",
backstory="You are an expert in WordPress operations and data analysis",
tools=wordpress_tools,
reasoning=True,
verbose=False
)
outlook_mail_agent = Agent(
role="Outlook Mail Specialist",
goal="Handle all Outlook Mail related tasks and data processing",
backstory="You are an expert in Outlook Mail operations and data analysis",
tools=outlook_mail_tools,
reasoning=True,
verbose=False
)
airtable_agent = Agent(
role="Airtable Specialist",
goal="Handle all Airtable related tasks and data processing",
backstory="You are an expert in Airtable operations and data analysis",
tools=airtable_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=wordpress_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=outlook_mail_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[wordpress_agent, outlook_mail_agent, airtable_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()
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