Create powerful collaborative AI workflows by connecting multiple MCP servers including Stripe, Google Docs, Dropbox for enhanced multi-agent automation capabilities in Klavis AI.
Stripe is a suite of payment APIs that powers commerce for online businesses
Google Docs is a word processor included as part of the free, web-based Google Docs Editors suite
Dropbox is a file hosting service that offers cloud storage and file synchronization
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"))
stripe_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.STRIPE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
google_docs_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_DOCS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
dropbox_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.DROPBOX,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
stripe_tools = MCPServerAdapter(stripe_mcp_instance.server_params)
google_docs_tools = MCPServerAdapter(google_docs_mcp_instance.server_params)
dropbox_tools = MCPServerAdapter(dropbox_mcp_instance.server_params)
# Create specialized agents for each service
stripe_agent = Agent(
role="Stripe Specialist",
goal="Handle all Stripe related tasks and data processing",
backstory="You are an expert in Stripe operations and data analysis",
tools=stripe_tools,
reasoning=True,
verbose=False
)
google_docs_agent = Agent(
role="Google Docs Specialist",
goal="Handle all Google Docs related tasks and data processing",
backstory="You are an expert in Google Docs operations and data analysis",
tools=google_docs_tools,
reasoning=True,
verbose=False
)
dropbox_agent = Agent(
role="Dropbox Specialist",
goal="Handle all Dropbox related tasks and data processing",
backstory="You are an expert in Dropbox operations and data analysis",
tools=dropbox_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=stripe_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=google_docs_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[stripe_agent, google_docs_agent, dropbox_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()
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