Connectto Stripe, Linear, Salesforce MCP Servers
Create powerful collaborative AI workflows by connecting multiple MCP servers including Stripe, Linear, Salesforce for enhanced multi-agent automation capabilities in Klavis AI.
Stripe
Stripe is a suite of payment APIs that powers commerce for online businesses
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
Salesforce
Salesforce is the world's leading customer relationship management (CRM) platform that helps businesses connect with customers, partners, and potential customers
Available Tools:
- salesforce_get_accounts
- salesforce_create_account
- salesforce_update_account
- +24 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"))
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,
)
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,
)
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,
)
# Initialize MCP tools for each server
stripe_tools = MCPServerAdapter(stripe_mcp_instance.server_params)
linear_tools = MCPServerAdapter(linear_mcp_instance.server_params)
salesforce_tools = MCPServerAdapter(salesforce_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
)
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
)
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
)
# 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=linear_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[stripe_agent, linear_agent, salesforce_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()Frequently Asked Questions
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