string_tools_client.py

# Create server parameters for stdio connection
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from langchain_mcp_adapters.tools import load_mcp_tools
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
import asyncio
from dotenv import load_dotenv
import os
load_dotenv()

model = ChatOpenAI(
  model="z-ai/glm-5.2",
  api_key=os.getenv("NVIDIA_API_KEY"), 
  base_url="https://integrate.api.nvidia.com/v1"
)

server_params = StdioServerParameters(
    command="python",
    # Make sure to update to the full absolute path to your math_server.py file
    args=["string_tools_mcp_server.py"],
)

async def run_agent():
    async with stdio_client(server_params) as (read, write):
        async with ClientSession(read, write) as session:
            # Initialize the connection
            await session.initialize()

            # Get tools
            tools = await load_mcp_tools(session)

            # Create and run the agent
            agent = create_react_agent(model, tools)
            agent_response_1 = await agent.ainvoke({"messages": "Reverse the string 'HelloWorld!"})
            agent_response_2 = await agent.ainvoke({"messages": "How many words are in the 'Arman is an AI Engineer'?"})
            for m in agent_response_1['messages']:
                m.pretty_print()
            print(f"Response 2 {'=' * 40}")
            for m in agent_response_2['messages']:
                m.pretty_print()

# Run the async function
if __name__ == "__main__":
    asyncio.run(run_agent())