Create powerful collaborative AI workflows by connecting multiple MCP servers including Close, Salesforce, Discord for enhanced multi-agent automation capabilities in Klavis AI.
Close is a modern CRM platform built for sales teams, providing powerful lead management, contact organization, and sales pipeline tracking to help businesses close more deals
Salesforce is the world's leading customer relationship management (CRM) platform that helps businesses connect with customers, partners, and potential customers
Discord is a VoIP and instant messaging social platform
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"))
close_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CLOSE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
salesforce_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.SALESFORCE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
discord_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.DISCORD,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
close_tools = MCPServerAdapter(close_mcp_instance.server_params)
salesforce_tools = MCPServerAdapter(salesforce_mcp_instance.server_params)
discord_tools = MCPServerAdapter(discord_mcp_instance.server_params)
# Create specialized agents for each service
close_agent = Agent(
role="Close Specialist",
goal="Handle all Close related tasks and data processing",
backstory="You are an expert in Close operations and data analysis",
tools=close_tools,
reasoning=True,
verbose=False
)
salesforce_agent = Agent(
role="Salesforce Specialist",
goal="Handle all Salesforce related tasks and data processing",
backstory="You are an expert in Salesforce operations and data analysis",
tools=salesforce_tools,
reasoning=True,
verbose=False
)
discord_agent = Agent(
role="Discord Specialist",
goal="Handle all Discord related tasks and data processing",
backstory="You are an expert in Discord operations and data analysis",
tools=discord_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=close_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=salesforce_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[close_agent, salesforce_agent, discord_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()
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