#!/usr/bin/env python3
"""
LangChain agent that uses Thenvoi MCP tools with langchain-mcp-adapters.
This example shows how to use the Thenvoi MCP server with a LangChain
agent using the newer create_agent pattern (built on LangGraph).
Usage:
export OPENAI_API_KEY="sk-..."
export THENVOI_API_KEY="thnv_..."
uv run examples/langchain_agent.py
"""
import asyncio
import logging
import os
from dotenv import load_dotenv
from langchain.agents import create_agent
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
load_dotenv()
logging.basicConfig(level=logging.INFO, format="%(message)s")
logger = logging.getLogger(__name__)
async def main() -> None:
"""Run LangChain agent with Thenvoi MCP tools."""
if not os.getenv("OPENAI_API_KEY") or not os.getenv("THENVOI_API_KEY"):
logger.error("Error: Set OPENAI_API_KEY and THENVOI_API_KEY")
return
project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
# Create MCP client that connects to Thenvoi server
client = MultiServerMCPClient(
{
"thenvoi": {
"command": "uv",
"args": ["--directory", project_root, "run", "thenvoi-mcp"],
"transport": "stdio",
"env": {
"THENVOI_API_KEY": os.getenv("THENVOI_API_KEY", ""),
"THENVOI_BASE_URL": os.getenv(
"THENVOI_BASE_URL", "https://app.thenvoi.com"
),
},
},
}
)
logger.info("Loading tools from Thenvoi MCP server...")
tools = await client.get_tools()
logger.info(f"Loaded {len(tools)} tools!")
# Create LLM
llm = ChatOpenAI(model="gpt-4o", temperature=0)
# Create the agent using LangChain's create_agent
# (This is the modern approach that uses LangGraph under the hood)
agent_executor = create_agent(llm, tools)
logger.info("\n" + "=" * 50)
logger.info("LangChain Agent Ready!")
logger.info("=" * 50)
logger.info("Type 'exit' to quit\n")
# Interactive loop
while True:
user_input = input("You: ").strip()
if not user_input:
continue
if user_input.lower() in ["exit", "quit", "q"]:
break
try:
result = await agent_executor.ainvoke({"messages": [("user", user_input)]})
# Get the last message from the agent
last_message = result["messages"][-1]
logger.info(f"\nAgent: {last_message.content}\n")
except Exception as e:
logger.error(f"\nError: {str(e)}\n")
if __name__ == "__main__":
asyncio.run(main())
