MCP vs API: rename folder to match slug and sync code with the article

mcp-vs-api-calls/README.md → mcp-vs-api/README.md

@@ -1,6 +1,6 @@
 # MCP vs API Calls: Which Should You Use for Python LLM Apps?
 
-This folder contains the sample code for the Real Python tutorial [MCP vs API Calls: Which Should You Use for Python LLM Apps?](https://realpython.com/mcp-vs-api-calls/).
+This folder contains the sample code for the Real Python tutorial [MCP vs API Calls: Which Should You Use for Python LLM Apps?](https://realpython.com/mcp-vs-api/).
 
 ## Files
 
@@ -16,7 +16,7 @@ Create a virtual environment and install the dependencies:
 ```console
 $ python -m venv tools-venv
 $ source tools-venv/bin/activate
-(tools-venv) $ python -m pip install anthropic "mcp>=2,<3"
+(tools-venv) $ python -m pip install "anthropic>=1,<2" "mcp>=2,<3"
 ```
 
 The examples use the Anthropic client, which requires an API key. Create a key in the [Anthropic Console](https://console.anthropic.com/), scope it to a single workspace, and export it:

mcp-vs-api-calls/client.py → mcp-vs-api/client.py

@@ -32,7 +32,7 @@ def ask_model(
 ) -> Message:
     return client.messages.create(
         model=model,
-        max_tokens=1024,
+        max_tokens=2048,
         tools=tools,
         messages=messages,
     )
@@ -45,14 +45,9 @@ async def run_tool(client: Client, block: ToolUseBlock) -> str:
 
 def tool_result(block: ToolUseBlock, output: str) -> dict:
     return {
-        "role": "user",
-        "content": [
-            {
-                "type": "tool_result",
-                "tool_use_id": block.id,
-                "content": output,
-            },
-        ],
+        "type": "tool_result",
+        "tool_use_id": block.id,
+        "content": output,
     }
 
 
@@ -63,15 +58,17 @@ async def main(server: StdioServerParameters) -> None:
         client = anthropic.Anthropic()
         messages = [{"role": "user", "content": QUESTION}]
         response = ask_model(client, messages, tools)
-        for block in response.content:
-            if block.type == "tool_use":
-                messages.append(
-                    {"role": "assistant", "content": response.content}
-                )
-                output = await run_tool(mcp, block)
-                messages.append(tool_result(block, output))
+
+        tool_uses = [b for b in response.content if b.type == "tool_use"]
+        if tool_uses:
+            messages.append({"role": "assistant", "content": response.content})
+            results = [
+                tool_result(b, await run_tool(mcp, b)) for b in tool_uses
+            ]
+            messages.append({"role": "user", "content": results})
+
         final = ask_model(client, messages, tools)
-        print(final.content[0].text)
+        print(next(b.text for b in final.content if b.type == "text"))
 
 
 if __name__ == "__main__":

mcp-vs-api-calls/client_api.py → mcp-vs-api/client_api.py

@@ -40,7 +40,7 @@ def ask_model(
 ) -> Message:
     return client.messages.create(
         model=model,
-        max_tokens=1024,
+        max_tokens=2048,
         tools=tools,
         messages=messages,
     )
@@ -53,29 +53,25 @@ def run_tool(block: ToolUseBlock) -> str:
 
 def tool_result(block: ToolUseBlock, output: str) -> dict:
     return {
-        "role": "user",
-        "content": [
-            {
-                "type": "tool_result",
-                "tool_use_id": block.id,
-                "content": output,
-            },
-        ],
+        "type": "tool_result",
+        "tool_use_id": block.id,
+        "content": output,
     }
 
 
 def main() -> None:
     client = anthropic.Anthropic()
     messages = [{"role": "user", "content": QUESTION}]
     response = ask_model(client, messages, TOOLS)
-    for block in response.content:
-        if block.type == "tool_use":
-            messages.append(
-                {"role": "assistant", "content": response.content},
-            )
-            messages.append(tool_result(block, run_tool(block)))
+
+    tool_uses = [b for b in response.content if b.type == "tool_use"]
+    if tool_uses:
+        messages.append({"role": "assistant", "content": response.content})
+        results = [tool_result(b, run_tool(b)) for b in tool_uses]
+        messages.append({"role": "user", "content": results})
+
     final = ask_model(client, messages, TOOLS)
-    print(final.content[0].text)
+    print(next(b.text for b in final.content if b.type == "text"))
 
 
 if __name__ == "__main__":