LangGraph

uv add langgraph langchain-mcp-adapters langchain-openai

import os
import asyncio
import base64
from langgraph.prebuilt import create_react_agent
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI

# Configure StackOne account
STACKONE_ACCOUNT_ID = "<account_id>"  # Your StackOne account ID

# Encode API key for Basic auth
auth_token = base64.b64encode(
    f"{os.getenv('STACKONE_API_KEY')}:".encode()
).decode()

async def main():
    # Connect to StackOne MCP server
    mcp_client = MultiServerMCPClient({
        "stackone": {
            "url": "https://api.stackone.com/mcp",
            "transport": "streamable_http",
            "headers": {
                "Authorization": f"Basic {auth_token}",
                "x-account-id": STACKONE_ACCOUNT_ID,
                "Content-Type": "application/json",
                "Accept": "application/json,text/event-stream",  # Required by MCP spec
                "MCP-Protocol-Version": "2025-06-18"
            }
        }
    })

    # Get StackOne tools
    tools = await mcp_client.get_tools()

    # Create LangGraph agent with StackOne tools
    agent = create_react_agent(
    ChatOpenAI(model="gpt-5"),
        tools=tools,
        state_modifier="You are a helpful assistant with access to data from connected platforms."
    )

    # Run agent
    for chunk in agent.stream({"messages": [("human", "Search recent calls in Gong")]}):
        print(chunk)

asyncio.run(main())

STACKONE_API_KEY=<stackone_api_key>
OPENAI_API_KEY=your_openai_key