The original example code (The Query Processing Logic in the MCP building tutorial site https://modelcontextprotocol.io/docs/2026-07-28/develop/build-client) has the following core issues:
- Single-turn Limitation: After the initial API call, the code only checks and processes tool_use blocks once. If Claude requests additional tool calls in its second response (e.g., needing to chain a second tool based on the output of the first), the original code fails to handle them—it simply ignores subsequent tool calls, causing complex multi-step tasks to fail.
- Lack of Agentic Loop Structure: It does not use a loop to continuously maintain conversation state. A correct implementation should, after each model response, check whether tool_use blocks are present; if so, execute the tools, append the results to the message history, and continue with the next API call—repeating this cycle until the model outputs a plain-text final answer.
The following corrected snippet resolves these issues by introducing a while True loop, correctly implementing a multi-turn tool-calling agent loop. Below is the corrected code version:
async def process_query(client, query: str) -> str:
messages = [
{"role": "user",
"content": query}
]
tool_list = await client.list_tools()
available_tools = [{
"name": tool.name,
"description": tool.description,
"input_schema": tool.input_schema,
} for tool in tool_list.tools]
final_texts = []
while True:
response = await anthropic.messages.create(
model=MODEL,
max_tokens=1000,
messages=messages,
tools=available_tools,
)
# Append the full assistant response back to the message history for context
messages.append({
"role": "assistant",
"content": response.content,
})
tool_uses = []
for block in response.content:
if block.type == "text":
final_texts.append(block.text)
elif block.type == "tool_use":
tool_uses.append(block)
# If no tool_use is requested, this is the final answer; exit the loop
if not tool_uses:
break
tool_results = []
for block in tool_uses:
try:
result = await client.call_tool(block.name, block.input)
tool_results.append({
"type": "tool_result",
"tool_use_id": block.id,
"content": format_tool_result(result), # Assumes format_tool_result is defined elsewhere
"is_error": bool(result.is_error),
})
except Exception as e:
# Tool execution errors must also be returned as tool_result to the model
tool_results.append({
"type": "tool_result",
"tool_use_id": block.id,
"content": f"Tool execution error: {e}",
"is_error": True,
})
# Feed the tool results back as a user message to continue the next turn
messages.append({
"role": "user",
"content": tool_results,
})
return "\n".join(final_texts)
(Note: format_tool_result is assumed to be a helper function that extracts text from the tool response, similar to "\n".join(block.text for block in result.content if isinstance(block, TextContent)) in the original code.)
The original example code (The Query Processing Logic in the MCP building tutorial site https://modelcontextprotocol.io/docs/2026-07-28/develop/build-client) has the following core issues:
The following corrected snippet resolves these issues by introducing a while True loop, correctly implementing a multi-turn tool-calling agent loop. Below is the corrected code version:
(Note: format_tool_result is assumed to be a helper function that extracts text from the tool response, similar to "\n".join(block.text for block in result.content if isinstance(block, TextContent)) in the original code.)