test fix

tests/pass_through_tests/test_mcp_routes.py

@@ -1,60 +1,35 @@
+# Create server parameters for stdio connection
 import asyncio
-from openai import AsyncOpenAI
-from openai.types.chat import ChatCompletionUserMessageParam
+import os
+
+from langchain_mcp_adapters.tools import load_mcp_tools
+from langchain_openai import ChatOpenAI
+from langgraph.prebuilt import create_react_agent
 from mcp import ClientSession
 from mcp.client.sse import sse_client
-from litellm.experimental_mcp_client.tools import (
-    transform_mcp_tool_to_openai_tool,
-    transform_openai_tool_call_request_to_mcp_tool_call_request,
-)
 
 
 async def main():
-    # Initialize clients
-    client = AsyncOpenAI(api_key="sk-1234", base_url="http://localhost:4000")
+    model = ChatOpenAI(model="gpt-4o", api_key="sk-12")
 
-    # Connect to MCP
-    async with sse_client("http://localhost:4000/mcp/") as (read, write):
+    async with sse_client(url="http://localhost:4000/mcp/") as (read, write):
         async with ClientSession(read, write) as session:
+            # Initialize the connection
+            print("Initializing session")
             await session.initialize()
-            mcp_tools = await session.list_tools()
-            print("List of MCP tools for MCP server:", mcp_tools.tools)
+            print("Session initialized")
 
-            # Create message
-            messages = [
-                ChatCompletionUserMessageParam(
-                    content="Send an email about LiteLLM supporting MCP", role="user"
-                )
-            ]
+            # Get tools
+            print("Loading tools")
+            tools = await load_mcp_tools(session)
+            print("Tools loaded")
+            print(tools)
 
-            # Request with tools
-            response = await client.chat.completions.create(
-                model="gpt-4o",
-                messages=messages,
-                tools=[
-                    transform_mcp_tool_to_openai_tool(tool) for tool in mcp_tools.tools
-                ],
-                tool_choice="auto",
-            )
-
-            # Handle tool call
-            if response.choices[0].message.tool_calls:
-                tool_call = response.choices[0].message.tool_calls[0]
-                if tool_call:
-                    # Convert format
-                    mcp_call = (
-                        transform_openai_tool_call_request_to_mcp_tool_call_request(
-                            openai_tool=tool_call.model_dump()
-                        )
-                    )
-
-                    # Execute tool
-                    result = await session.call_tool(
-                        name=mcp_call.name, arguments=mcp_call.arguments
-                    )
-
-                    print("Result:", result)
+            # # Create and run the agent
+            # agent = create_react_agent(model, tools)
+            # agent_response = await agent.ainvoke({"messages": "what's (3 + 5) x 12?"})
 
 
-# Run it
-asyncio.run(main())
+# Run the async function
+if __name__ == "__main__":
+    asyncio.run(main())