Connectto Attio, YouTube, Linear MCP Servers
Create powerful collaborative AI workflows by connecting multiple MCP servers including Attio, YouTube, Linear for enhanced multi-agent automation capabilities in Klavis AI.
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
YouTube
Extract and convert YouTube video information to markdown format
Available Tools:
- get_youtube_video_transcript
Linear
Linear is a modern issue tracking and project management tool designed for high-performance teams to build better software faster
Available Tools:
- linear_get_teams
- linear_get_issues
- linear_get_issue_by_id
- +9 more tools
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"))
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,
)
youtube_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.YOUTUBE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
linear_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.LINEAR,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
attio_tools = MCPServerAdapter(attio_mcp_instance.server_params)
youtube_tools = MCPServerAdapter(youtube_mcp_instance.server_params)
linear_tools = MCPServerAdapter(linear_mcp_instance.server_params)
# Create specialized agents for each service
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
)
youtube_agent = Agent(
role="YouTube Specialist",
goal="Handle all YouTube related tasks and data processing",
backstory="You are an expert in YouTube operations and data analysis",
tools=youtube_tools,
reasoning=True,
verbose=False
)
linear_agent = Agent(
role="Linear Specialist",
goal="Handle all Linear related tasks and data processing",
backstory="You are an expert in Linear operations and data analysis",
tools=linear_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=attio_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=youtube_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[attio_agent, youtube_agent, linear_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()Frequently Asked Questions
Everything you need to know about connecting CrewAI to these MCP servers
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