Improve FastAPI section narratives

Author: lara-openai

examples/mcp/databricks_mcp_cookbook.ipynb

@@ -454,8 +454,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The [api_server.py](https://github.com/openai/openai-cookbook/blob/main/examples/mcp/building-a-supply-chain-copilot-with-agent-sdk-and-databricks-mcp/api_server.py) is a FastAPI backend that exposes your agent as a streaming /chat API endpoint. At startup it configures CORS so a local front-end can talk to it, then defines `build_mcp_servers()`, which authenticates to the caller’s Databricks workspace, constructs two HTTP “server tools” (one for vector search, one for Unity-Catalog functions), and pre-connects them for low-latency use. Each incoming POST to /chat contains a single user message. The handler spins up a fresh Agent whose mcp_servers list is populated by those streaming tools and whose model is forced to call a tool for every turn. \n",
-    "\n",
     "To kick off the backend (Fast API), run the following command: "
    ]
   },
@@ -472,7 +470,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The API will be available at http://localhost:8000 (for FastAPI docs go to: http://localhost:8000/docs). "
+    "The API will be available at http://localhost:8000 (for FastAPI docs go to: http://localhost:8000/docs). \n",
+    "\n",
+    "The [api_server.py](https://github.com/openai/openai-cookbook/blob/main/examples/mcp/building-a-supply-chain-copilot-with-agent-sdk-and-databricks-mcp/api_server.py) is a FastAPI backend that exposes your agent as a streaming /chat API endpoint. At startup it configures CORS so a local front-end can talk to it, then defines `build_mcp_servers()`, which authenticates to the caller’s Databricks workspace, constructs two HTTP “server tools” (one for vector search, one for Unity-Catalog functions), and pre-connects them for low-latency use. Each incoming POST to /chat contains a single user message. The handler spins up a fresh Agent whose mcp_servers list is populated by those streaming tools and whose model is forced to call a tool for every turn. "
    ]
   },
   {