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1. jayanthma commented on Mar 27, 2025

   

   jayanthma

   on Mar 27, 2025

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   Hi @isakulaksiz , the issue was persisting in the jupyter notebook so I converted it to .py and it ran successfully. Find the code below.

   from langchain_mcp_adapters.client import MultiServerMCPClient

   from langgraph.prebuilt import create_react_agent

   from langchain_aws import ChatBedrockConverse
   import boto3

   bedrock_client=boto3.client(service_name='bedrock-runtime', region_name="us-east-1")

   model = ChatBedrockConverse(
   client=bedrock_client,
   model="us.meta.llama3-3-70b-instruct-v1:0",
   temperature=0,
   )

   async def test_mcp_client():
   async with MultiServerMCPClient(
   {
   "math": {
   "command": "C:/Users/jay/coding_projects/LangGraph/venv/Scripts/python.exe",

   Make sure to update to the full absolute path to your math_server.py file

   "args": ["C:/Users/jay/coding_projects/LangGraph/mcp/math_server.py"],
   "transport": "stdio",
   },
   "weather": {

   make sure you start your weather server on port 8000

   "url": "http://localhost:8000/sse",
   "transport": "sse",
   }
   }
   ) as client:
   tools = client.get_tools()
   print("Tools: ", tools)
   agent = create_react_agent(model, client.get_tools(), debug=True)
   math_response = await agent.ainvoke({"messages": "what's 3*175"})
   weather_response = await agent.ainvoke({"messages": "what is the weather in nyc?"})

   return math_response, weather_response
   if name == "main":
   import asyncio
   math_response, weather_response = asyncio.run(test_mcp_client())
   print(math_response)
   print(weather_response)

   Hope it helps!!
2. isakulaksiz

   closed this as completedon Apr 3, 2025