cleanup

jssmith · jssmith · commit eba0ab8bd179 · 2025-09-20T10:10:06.000-07:00
diff --git a/openai_agents/mcp/README.md b/openai_agents/mcp/README.md
@@ -9,22 +9,22 @@ Before running these examples, be sure to review the [prerequisites and backgrou
 
 ## Running the Examples
 
-### File System MCP - Stateless
+### Stdio MCP
 
 First, start the worker:
 ```bash
-uv run openai_agents/mcp/run_file_system_stateless_worker.py
+uv run openai_agents/mcp/run_file_system_worker.py
 ```
 
 Run the workflow:
 ```bash
-uv run openai_agents/mcp/run_file_system_stateless_workflow.py
+uv run openai_agents/mcp/run_file_system_workflow.py
 ```
 
 This sample assumes that the worker and `run_file_system_workflow.py` are on the same machine.
 
 
-### Streamable HTTP MCP - Stateless
+### Streamable HTTP MCP
 
 First, start the worker:
 ```bash
@@ -33,15 +33,15 @@ uv run openai_agents/mcp/servers/tools_server.py --transport=streamable-http
 
 Then start the worker:
 ```bash
-uv run openai_agents/mcp/run_streamable_http_stateless_worker.py
+uv run openai_agents/mcp/run_streamable_http_worker.py
 ```
 
 Finally, run the workflow:
 ```bash
-uv run openai_agents/mcp/run_streamable_http_stateless_workflow.py
+uv run openai_agents/mcp/run_streamable_http_workflow.py
 ```
 
-### SSE MCP - Stateless
+### SSE MCP
 
 First, start the MCP server:
 ```bash
@@ -50,15 +50,15 @@ uv run openai_agents/mcp/servers/tools_server.py --transport=sse
 
 Then start the worker:
 ```bash
-uv run openai_agents/mcp/run_sse_stateless_worker.py
+uv run openai_agents/mcp/run_sse_worker.py
 ```
 
 Finally, run the workflow:
 ```bash
-uv run openai_agents/mcp/run_sse_stateless_workflow.py
+uv run openai_agents/mcp/run_sse_workflow.py
 ```
 
-### Prompt Server MCP - Stateless
+### Prompt Server MCP
 
 First, start the MCP server:
 ```bash
@@ -67,22 +67,22 @@ uv run openai_agents/mcp/servers/prompt_server.py
 
 Then start the worker:
 ```bash
-uv run openai_agents/mcp/run_prompt_server_stateless_worker.py
+uv run openai_agents/mcp/run_prompt_server_worker.py
 ```
 
 Finally, run the workflow:
 ```bash
-uv run openai_agents/mcp/run_prompt_server_stateless_workflow.py
+uv run openai_agents/mcp/run_prompt_server_workflow.py
 ```
 
 
-### Memory MCP - Stateful (Research Scratchpad)
+### Memory MCP (Research Scratchpad)
 
 Demonstrates durable note-taking with the Memory MCP server: write seed notes, query by tags, synthesize a brief with citations, then update and delete notes.
 
 Start the worker:
 ```bash
-uv run openai_agents/mcp/run_memory_stateful_worker.py
+uv run openai_agents/mcp/run_memory_worker.py
 ```
 
 Run the research scratchpad workflow:
diff --git a/openai_agents/mcp/run_file_system_worker.py b/openai_agents/mcp/run_file_system_worker.py
@@ -14,9 +14,7 @@
 )
 from temporalio.worker import Worker
 
-from openai_agents.mcp.workflows.file_system_stateless_workflow import (
-    FileSystemWorkflow,
-)
+from openai_agents.mcp.workflows.file_system_workflow import FileSystemWorkflow
 
 
 async def main():
@@ -49,7 +47,7 @@ async def main():
 
     worker = Worker(
         client,
-        task_queue=f"openai-agents-mcp-filesystem-stateless-task-queue",
+        task_queue=f"openai-agents-mcp-filesystem-task-queue",
         workflows=[
             FileSystemWorkflow,
         ],
diff --git a/openai_agents/mcp/run_file_system_workflow.py b/openai_agents/mcp/run_file_system_workflow.py
@@ -3,9 +3,7 @@
 from temporalio.client import Client
 from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
 
-from openai_agents.mcp.workflows.file_system_stateless_workflow import (
-    FileSystemWorkflow,
-)
+from openai_agents.mcp.workflows.file_system_workflow import FileSystemWorkflow
 
 
 async def main():
@@ -20,8 +18,8 @@ async def main():
     # Execute a workflow
     result = await client.execute_workflow(
         FileSystemWorkflow.run,
-        id="file-system-stateless-workflow",
-        task_queue="openai-agents-mcp-filesystem-stateless-task-queue",
+        id="file-system-workflow",
+        task_queue="openai-agents-mcp-filesystem-task-queue",
     )
 
     print(f"Result: {result}")
diff --git a/openai_agents/mcp/run_memory_research_scratchpad_workflow.py b/openai_agents/mcp/run_memory_research_scratchpad_workflow.py
@@ -19,7 +19,7 @@ async def main():
     result = await client.execute_workflow(
         MemoryResearchScratchpadWorkflow.run,
         id="memory-research-scratchpad-workflow",
-        task_queue="openai-agents-mcp-memory-stateful-task-queue",
+        task_queue="openai-agents-mcp-memory-task-queue",
     )
 
     print(f"Result:\n{result}")
diff --git a/openai_agents/mcp/run_memory_worker.py b/openai_agents/mcp/run_memory_worker.py
@@ -46,7 +46,7 @@ async def main():
 
     worker = Worker(
         client,
-        task_queue="openai-agents-mcp-memory-stateful-task-queue",
+        task_queue="openai-agents-mcp-memory-task-queue",
         workflows=[
             MemoryResearchScratchpadWorkflow,
         ],
diff --git a/openai_agents/mcp/run_prompt_server_worker.py b/openai_agents/mcp/run_prompt_server_worker.py
@@ -13,9 +13,7 @@
 )
 from temporalio.worker import Worker
 
-from openai_agents.mcp.workflows.prompt_server_stateless_workflow import (
-    PromptServerWorkflow,
-)
+from openai_agents.mcp.workflows.prompt_server_workflow import PromptServerWorkflow
 
 
 async def main():
@@ -48,7 +46,7 @@ async def main():
 
         worker = Worker(
             client,
-            task_queue="openai-agents-mcp-prompt-stateless-task-queue",
+            task_queue="openai-agents-mcp-prompt-task-queue",
             workflows=[
                 PromptServerWorkflow,
             ],
diff --git a/openai_agents/mcp/run_prompt_server_workflow.py b/openai_agents/mcp/run_prompt_server_workflow.py
@@ -5,9 +5,7 @@
 from temporalio.client import Client
 from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
 
-from openai_agents.mcp.workflows.prompt_server_stateless_workflow import (
-    PromptServerWorkflow,
-)
+from openai_agents.mcp.workflows.prompt_server_workflow import PromptServerWorkflow
 
 
 async def main():
@@ -21,7 +19,7 @@ async def main():
     result = await client.execute_workflow(
         PromptServerWorkflow.run,
         id="prompt-server-workflow",
-        task_queue="openai-agents-mcp-prompt-stateless-task-queue",
+        task_queue="openai-agents-mcp-prompt-task-queue",
     )
 
     print(f"Result: {result}")
diff --git a/openai_agents/mcp/run_sse_worker.py b/openai_agents/mcp/run_sse_worker.py
@@ -13,7 +13,7 @@
 )
 from temporalio.worker import Worker
 
-from openai_agents.mcp.workflows.sse_stateless_workflow import SseWorkflow
+from openai_agents.mcp.workflows.sse_workflow import SseWorkflow
 
 
 async def main():
@@ -46,7 +46,7 @@ async def main():
 
         worker = Worker(
             client,
-            task_queue="openai-agents-mcp-sse-stateless-task-queue",
+            task_queue="openai-agents-mcp-sse-task-queue",
             workflows=[
                 SseWorkflow,
             ],
diff --git a/openai_agents/mcp/run_sse_workflow.py b/openai_agents/mcp/run_sse_workflow.py
@@ -5,7 +5,7 @@
 from temporalio.client import Client
 from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
 
-from openai_agents.mcp.workflows.sse_stateless_workflow import SseWorkflow
+from openai_agents.mcp.workflows.sse_workflow import SseWorkflow
 
 
 async def main():
@@ -18,8 +18,8 @@ async def main():
     # Execute a workflow
     result = await client.execute_workflow(
         SseWorkflow.run,
-        id="sse-stateless-workflow",
-        task_queue="openai-agents-mcp-sse-stateless-task-queue",
+        id="sse-workflow",
+        task_queue="openai-agents-mcp-sse-task-queue",
     )
 
     print(f"Result: {result}")
diff --git a/openai_agents/mcp/run_streamable_http_worker.py b/openai_agents/mcp/run_streamable_http_worker.py
@@ -13,9 +13,7 @@
 )
 from temporalio.worker import Worker
 
-from openai_agents.mcp.workflows.streamable_http_stateless_workflow import (
-    StreamableHttpWorkflow,
-)
+from openai_agents.mcp.workflows.streamable_http_workflow import StreamableHttpWorkflow
 
 
 async def main():
@@ -48,7 +46,7 @@ async def main():
 
         worker = Worker(
             client,
-            task_queue="openai-agents-mcp-streamable-http-stateless-task-queue",
+            task_queue="openai-agents-mcp-streamable-http-task-queue",
             workflows=[
                 StreamableHttpWorkflow,
             ],
diff --git a/openai_agents/mcp/run_streamable_http_workflow.py b/openai_agents/mcp/run_streamable_http_workflow.py
@@ -5,9 +5,7 @@
 from temporalio.client import Client
 from temporalio.contrib.openai_agents import OpenAIAgentsPlugin
 
-from openai_agents.mcp.workflows.streamable_http_stateless_workflow import (
-    StreamableHttpWorkflow,
-)
+from openai_agents.mcp.workflows.streamable_http_workflow import StreamableHttpWorkflow
 
 
 async def main():
@@ -20,8 +18,8 @@ async def main():
     # Execute a workflow
     result = await client.execute_workflow(
         StreamableHttpWorkflow.run,
-        id="streamable-http-stateless-workflow",
-        task_queue="openai-agents-mcp-streamable-http-stateless-task-queue",
+        id="streamable-http-workflow",
+        task_queue="openai-agents-mcp-streamable-http-task-queue",
     )
 
     print(f"Result: {result}")
diff --git a/openai_agents/mcp/servers/prompt_server.py b/openai_agents/mcp/servers/prompt_server.py
@@ -33,5 +33,26 @@ def generate_code_review_instructions(
 Use the available tools to check current time if you need timestamps for your analysis."""
 
 
+@mcp.prompt()
+def generate_review_rubric(target: str = "application code") -> str:
+    """Generate a scoring rubric for reviewing code or plans"""
+    return f"""You are evaluating {target}. Score each category 1-5 and justify briefly.
+
+CATEGORIES:
+- Correctness and Reliability
+- Security and Risk
+- Performance and Efficiency
+- Readability and Maintainability
+- Testability and Coverage
+- Compliance with Style/Guidelines
+
+FORMAT:
+- Overall Score (1-5)
+- Category Scores (bulleted)
+- Top 3 Issues (with impact level and suggested fix)
+- Quick Wins (3 bullets)
+"""
+
+
 if __name__ == "__main__":
     mcp.run(transport="streamable-http")
diff --git a/openai_agents/mcp/workflows/file_system_workflow.py b/openai_agents/mcp/workflows/file_system_workflow.py
diff --git a/openai_agents/mcp/workflows/prompt_server_workflow.py b/openai_agents/mcp/workflows/prompt_server_workflow.py
@@ -2,7 +2,6 @@
 
 from agents import Agent, Runner, trace
 from agents.mcp import MCPServer
-from agents.model_settings import ModelSettings
 from temporalio import workflow
 from temporalio.contrib import openai_agents
 
@@ -11,18 +10,24 @@
 class PromptServerWorkflow:
     @workflow.run
     async def run(self) -> str:
-        with trace(workflow_name="MCP Prompt Server Example"):
+        with trace(workflow_name="Prompt Server Example"):
+            outputs: list[str] = []
             server: MCPServer = openai_agents.workflow.stateless_mcp_server(
                 "PromptServer"
             )
 
             # Show available prompts
             workflow.logger.info("=== AVAILABLE PROMPTS ===")
+            outputs.append("=== AVAILABLE PROMPTS ===")
             prompts_result = await server.list_prompts()
             workflow.logger.info("User can select from these prompts:")
+            outputs.append("User can select from these prompts:")
             for i, prompt in enumerate(prompts_result.prompts, 1):
-                workflow.logger.info(f"  {i}. {prompt.name} - {prompt.description}")
+                line = f"  {i}. {prompt.name} - {prompt.description}"
+                workflow.logger.info(line)
+                outputs.append(line)
             workflow.logger.info("")
+            outputs.append("")
 
             # Demo code review with user-selected prompt
             workflow.logger.info("=== CODE REVIEW DEMO ===")
@@ -37,19 +42,23 @@ async def run(self) -> str:
                     {"focus": "security vulnerabilities", "language": "python"},
                 )
                 content = prompt_result.messages[0].content
-                if hasattr(content, "text"):
-                    instructions = content.text
-                else:
-                    instructions = str(content)
+                instructions = (
+                    content.text if hasattr(content, "text") else str(content)
+                )
                 workflow.logger.info("Generated instructions")
+                preview = instructions[:200].replace("\n", " ") + (
+                    "..." if len(instructions) > 200 else ""
+                )
+                outputs.append("=== INSTRUCTIONS (PREVIEW) ===")
+                outputs.append(preview)
             except Exception as e:
                 workflow.logger.info(f"Failed to get instructions: {e}")
                 instructions = f"You are a helpful assistant. Error: {e}"
+                outputs.append(f"Failed to get instructions: {e}")
 
             agent = Agent(
                 name="Code Reviewer Agent",
                 instructions=instructions,
-                model_settings=ModelSettings(tool_choice="auto"),
             )
 
             message = """Please review this code:
@@ -62,8 +71,9 @@ def process_user_input(user_input):
 """
 
             workflow.logger.info(f"Running: {message[:60]}...")
+            outputs.append("=== REVIEW OUTPUT ===")
             result = await Runner.run(starting_agent=agent, input=message)
             workflow.logger.info(result.final_output)
+            outputs.append(result.final_output)
             workflow.logger.info("\n" + "=" * 50 + "\n")
-
-            return "Prompt server demo completed successfully"
+            return "\n".join(outputs)
diff --git a/openai_agents/mcp/workflows/sse_workflow.py b/openai_agents/mcp/workflows/sse_workflow.py
@@ -11,7 +11,7 @@
 class SseWorkflow:
     @workflow.run
     async def run(self) -> str:
-        with trace(workflow_name="MCP SSE Example"):
+        with trace(workflow_name="SSE Example"):
             server: MCPServer = openai_agents.workflow.stateless_mcp_server("SseServer")
             agent = Agent(
                 name="Assistant",
diff --git a/openai_agents/mcp/workflows/streamable_http_workflow.py b/openai_agents/mcp/workflows/streamable_http_workflow.py
@@ -11,7 +11,7 @@
 class StreamableHttpWorkflow:
     @workflow.run
     async def run(self) -> str:
-        with trace(workflow_name="MCP Streamable HTTP Example"):
+        with trace(workflow_name="Streamable HTTP Example"):
             server: MCPServer = openai_agents.workflow.stateless_mcp_server(
                 "StreamableHttpServer"
             )

Original file line number	Diff line number	Diff line change
`@@ -19,7 +19,7 @@ async def main():`
`19`	`19`	`result = await client.execute_workflow(`
`20`	`20`	`MemoryResearchScratchpadWorkflow.run,`
`21`	`21`	`id="memory-research-scratchpad-workflow",`
`22`		`- task_queue="openai-agents-mcp-memory-stateful-task-queue",`
	`22`	`+ task_queue="openai-agents-mcp-memory-task-queue",`
`23`	`23`	`)`
`24`	`24`
`25`	`25`	`print(f"Result:\n{result}")`