add tag: mcp-server-track

README.md

@@ -8,6 +8,7 @@ sdk_version: 5.33.0
 app_file: app.py
 pinned: false
 short_description: A Gradio Application that uses Agentic AI to plan travels
+tag: mcp-server-track
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -104,7 +104,7 @@ def search_hotels(
 
 
 with gr.Blocks(title="Travel Itinerary MCP Server") as app:
-    gr.Markdown("# Travel Itinerary MCP Server")
+    gr.Markdown("# Travel Itinerary MCP Server\nThis application allows users to search for flights and hotels using the Google Flights and Google Hotels APIs via SerpAPI.")
     with gr.Tab("Search Flights"):
         gr.Interface(
             fn=search_flights,

script.py

@@ -1,57 +0,0 @@
-import asyncio
-import os
-from dotenv import load_dotenv
-import openai
-from agents import Agent, Runner, AsyncOpenAI, OpenAIChatCompletionsModel
-from agents.mcp import MCPServerSse
-import json
-
-# Load environment
-load_dotenv()
-
-# Set API key
-openai.api_key = os.getenv("NEBIUS_API_KEY")
-openai.base_url = "https://api.studio.nebius.com/v1/"
-
-# MCP tool URL (replace with actual URL you got from step 4.3)
-TOOL_URL = "http://127.0.0.1:7860/gradio_api/mcp/sse"
-
-async def main():
-    mcp_server = MCPServerSse({"url": TOOL_URL})
-
-    try:
-        await mcp_server.connect()
-
-        # Create an agent and register the connected tool
-        # ✅ Replace "MCP Agent" with a descriptive name if desired
-        # ✅ Update instructions to guide the agent's behavior
-        agent = Agent(
-            name="MCP Agent",
-            instructions="You help the user complete tasks using the connected tool.",
-            mcp_servers=[mcp_server],
-            model=OpenAIChatCompletionsModel( 
-                model="Qwen/Qwen3-235B-A22B",
-                openai_client=AsyncOpenAI(base_url="https://api.studio.nebius.com/v1/", api_key=os.getenv("NEBIUS_API_KEY"))
-            )
-        )
-
-        # 🔁 Replace this task with your actual prompt or goal
-        task = "You are a helpful assistant. Use the connected tool to assist with tasks. Read and analyse the tool output, focusing on key information and help the user in the following task:" \
-        "I want to travel from Hyderabad to Phuket from 5th July to 23rd July in 2025, please help me with my flight search, what are my cheapest and fastest options."
-
-        result = await Runner.run(agent, task)
-
-        print(result.final_output)
-        # print(json.dumps(result.new_items, indent=4))
-        # print(result.raw_responses)
-
-        # for r in result:
-        #     print(r)
-        #     print("\n============\n")
-
-    finally:
-        await mcp_server.cleanup()
-
-# Run the async main function
-if __name__ == "__main__":
-    asyncio.run(main())