Create powerful AI workflows by connecting multiple MCP servers including Close, Linear, Resend for enhanced 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
Linear is a modern issue tracking and project management tool designed for high-performance teams to build better software faster
Resend is a modern email API for sending and receiving emails programmatically
Follow these steps to connect LangChain to these MCP servers
Sign up for KlavisAI to access our MCP server management platform.
Add your desired MCP servers to LangChain and configure authentication settings.
Verify your connections work correctly and start using your enhanced AI capabilities.
import os
import asyncio
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
llm = ChatOpenAI(model="gpt-4o-mini", api_key=os.getenv("OPENAI_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,
)
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,
)
resend_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.RESEND,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
mcp_client = MultiServerMCPClient({
"close": {
"transport": "streamable_http",
"url": close_mcp_instance.server_url
},
"linear": {
"transport": "streamable_http",
"url": linear_mcp_instance.server_url
},
"resend": {
"transport": "streamable_http",
"url": resend_mcp_instance.server_url
}
})
tools = asyncio.run(mcp_client.get_tools())
agent = create_react_agent(
model=llm,
tools=tools,
)
response = asyncio.run(agent.ainvoke({
"messages": [{"role": "user", "content": "Your query here"}]
}))
Everything you need to know about connecting to these MCP servers
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