mcp sentiment analysis host

.gitignore

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+.env

host.py

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+import gradio as gr
+import json
+import os
+from dotenv import load_dotenv
+
+
+from smolagents import InferenceClientModel, CodeAgent, MCPClient
+
+load_dotenv()
+
+try:
+    mcp_client = MCPClient(
+        {
+            "url": "https://vikaskapur-mcp-server-sentiment.hf.space/gradio_api/mcp/sse",
+            "transport": 'sse'
+        }
+    )
+    tools = mcp_client.get_tools()
+
+
+    # Print tools in a readable format
+    print("Tools retrieved:")
+    print("\n".join(f"{t.name}: {t.description}" for t in tools))
+
+    model = InferenceClientModel(token=os.getenv("HUGGINGFACE_API_TOKEN"))
+    print(f"Model: {model.model_id}")
+
+    agent = CodeAgent(tools=[*tools], model=model, additional_authorized_imports=["json", "ast", "urllib", "base64"])
+
+    demo = gr.ChatInterface(
+        fn=lambda message, history: str(agent.run(message)),
+        type="messages",
+        examples=["Analyze the sentiment of the following text 'This is awesome'"],
+        title="Agent with MCP Tools",
+        description="This is a simple agent that uses MCP tools to answer questions.",
+    )
+
+    demo.launch()
+finally:
+    mcp_client.disconnect()

requirements.txt

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+python-dotenv
+gradio[mcp]
+smolagents[mcp]