Fix: Fix app workflows list-runs request & presentation

examples/basic/mcp_basic_agent/main.py

@@ -46,12 +46,13 @@
 # or loaded from mcp_agent.config.yaml/mcp_agent.secrets.yaml
 app = MCPApp(name="mcp_basic_agent")  # settings=settings)
 
+
 @app.tool()
-async def example_usage()->str:
+async def example_usage() -> str:
     """
-    An example function/tool that uses an agent with access to the fetch and filesystem 
-    mcp servers. The agent will read the contents of mcp_agent.config.yaml, print the 
-    first 2 paragraphs of the mcp homepage, and summarize the paragraphs into a tweet. 
+    An example function/tool that uses an agent with access to the fetch and filesystem
+    mcp servers. The agent will read the contents of mcp_agent.config.yaml, print the
+    first 2 paragraphs of the mcp homepage, and summarize the paragraphs into a tweet.
     The example uses both OpenAI, Anthropic, and simulates a multi-turn conversation.
     """
     async with app.run() as agent_app:
@@ -113,6 +114,7 @@ async def example_usage()->str:
 
     return result
 
+
 async def display_token_summary(app_ctx: MCPApp, agent: Agent | None = None):
     """Display comprehensive token usage summary using app/agent convenience APIs."""
     summary: TokenSummary = await app_ctx.get_token_summary()

examples/basic/mcp_model_selector/main.py

@@ -10,8 +10,9 @@
 app = MCPApp(name="llm_selector")
 model_selector = ModelSelector()
 
+
 @app.tool
-async def example_usage()->str:
+async def example_usage() -> str:
     """
     An example function/tool that demonstrates MCP's ModelPreferences type
     to select a model based on speed, cost, and intelligence priorities.
@@ -31,7 +32,7 @@ async def example_usage()->str:
         "Smartest OpenAI model:",
         data={"model_preferences": model_preferences, "model": model},
     )
-    result+="Smartest OpenAI model: " + model.name
+    result += "Smartest OpenAI model: " + model.name
 
     model_preferences = ModelPreferences(
         costPriority=0.25, speedPriority=0.25, intelligencePriority=0.5
@@ -44,7 +45,7 @@ async def example_usage()->str:
         "Most balanced OpenAI model:",
         data={"model_preferences": model_preferences, "model": model},
     )
-    result+="\nMost balanced OpenAI model: " + model.name
+    result += "\nMost balanced OpenAI model: " + model.name
 
     model_preferences = ModelPreferences(
         costPriority=0.3, speedPriority=0.6, intelligencePriority=0.1
@@ -57,7 +58,7 @@ async def example_usage()->str:
         "Fastest and cheapest OpenAI model:",
         data={"model_preferences": model_preferences, "model": model},
     )
-    result+="\nFastest and cheapest OpenAI model: " + model.name
+    result += "\nFastest and cheapest OpenAI model: " + model.name
 
     model_preferences = ModelPreferences(
         costPriority=0.1, speedPriority=0.1, intelligencePriority=0.8
@@ -70,7 +71,7 @@ async def example_usage()->str:
         "Smartest Anthropic model:",
         data={"model_preferences": model_preferences, "model": model},
     )
-    result+="\nSmartest Anthropic model: " + model.name
+    result += "\nSmartest Anthropic model: " + model.name
 
     model_preferences = ModelPreferences(
         costPriority=0.8, speedPriority=0.1, intelligencePriority=0.1
@@ -83,7 +84,7 @@ async def example_usage()->str:
         "Cheapest Anthropic model:",
         data={"model_preferences": model_preferences, "model": model},
     )
-    result+="\nCheapest Anthropic model: " + model.name
+    result += "\nCheapest Anthropic model: " + model.name
 
     model_preferences = ModelPreferences(
         costPriority=0.1,
@@ -101,7 +102,7 @@ async def example_usage()->str:
         "Select fastest model between gpt-4o/mini/sonnet/haiku:",
         data={"model_preferences": model_preferences, "model": model},
     )
-    result+="\nSelect fastest model between gpt-4o/mini/sonnet/haiku: " + model.name
+    result += "\nSelect fastest model between gpt-4o/mini/sonnet/haiku: " + model.name
 
     model_preferences = ModelPreferences(
         costPriority=0.15,
@@ -119,7 +120,7 @@ async def example_usage()->str:
         "Most balanced model between gpt-4o/mini/sonnet/haiku:",
         data={"model_preferences": model_preferences, "model": model},
     )
-    result+="\nMost balanced model between gpt-4o/mini/sonnet/haiku: " + model.name
+    result += "\nMost balanced model between gpt-4o/mini/sonnet/haiku: " + model.name
 
     # Examples showcasing new filtering capabilities
     print("\n[bold cyan]Testing new filtering capabilities:[/bold cyan]")
@@ -139,7 +140,7 @@ async def example_usage()->str:
             "context_window": model.context_window,
         },
     )
-    result+="\nBest model with context window >100k tokens: " + model.name
+    result += "\nBest model with context window >100k tokens: " + model.name
 
     # Example 2: Models with tool calling support
     model_preferences = ModelPreferences(
@@ -156,7 +157,7 @@ async def example_usage()->str:
             "tool_calling": model.tool_calling,
         },
     )
-    result+="\nBest model with tool calling support: " + model.name
+    result += "\nBest model with tool calling support: " + model.name
 
     # Example 3: Models with structured outputs (JSON mode)
     model_preferences = ModelPreferences(
@@ -173,7 +174,7 @@ async def example_usage()->str:
             "structured_outputs": model.structured_outputs,
         },
     )
-    result+="\nBest model with structured outputs support: " + model.name
+    result += "\nBest model with structured outputs support: " + model.name
 
     # Example 4: Models with medium context window (50k-150k tokens) and tool calling
     model_preferences = ModelPreferences(
@@ -194,7 +195,9 @@ async def example_usage()->str:
             "tool_calling": model.tool_calling,
         },
     )
-    result+="\nBest model with 50k-150k context window and tool calling: " + model.name    
+    result += (
+        "\nBest model with 50k-150k context window and tool calling: " + model.name
+    )
 
     # Example 5: Fast models with both tool calling and structured outputs
     model_preferences = ModelPreferences(
@@ -213,9 +216,12 @@ async def example_usage()->str:
             "speed": model.metrics.speed.tokens_per_second,
         },
     )
-    result+="\nFastest model with both tool calling and structured outputs: " + model.name
+    result += (
+        "\nFastest model with both tool calling and structured outputs: " + model.name
+    )
+
+    return result
 
-    return result  
 
 if __name__ == "__main__":
     import time

src/mcp_agent/cli/cloud/commands/app/workflows/main.py

@@ -5,11 +5,9 @@
 
 import typer
 from rich.console import Group
-from rich.padding import Padding
 from rich.panel import Panel
 from rich.prompt import Prompt
 from rich.syntax import Syntax
-from rich.table import Table
 from rich.text import Text
 
 from mcp_agent.cli.auth import load_api_key_credentials
@@ -245,16 +243,12 @@ def get_start_time(run: WorkflowRun):
             reverse=True,
         )
 
-        table = Table(title="Workflow Runs", show_lines=False, border_style="blue")
-        table.add_column("Name", style="white", overflow="fold")
-        table.add_column("Workflow ID", style="bold cyan", no_wrap=True)
-        table.add_column("Run ID", style="blue", overflow="fold")
-        table.add_column("Status", overflow="fold")
-        table.add_column("Start Time", style="magenta", overflow="fold")
-        table.add_column("End Time", style="yellow", overflow="fold")
+        console.print(f"\n[bold blue] Workflow Runs ({len(sorted_runs)})[/bold blue]")
+
+        for i, run in enumerate(sorted_runs):
+            if i > 0:
+                console.print()
 
-        for idx, run in enumerate(sorted_runs):
-            is_last_row = idx == len(sorted_runs) - 1
             start = getattr(run.temporal, "start_time", None)
             start_str = (
                 datetime.fromtimestamp(start).strftime("%Y-%m-%d %H:%M:%S")
@@ -271,22 +265,31 @@ def get_start_time(run: WorkflowRun):
 
             status = run.status.lower()
             if status == "completed":
-                status_text = f"[green]{status}[/green]"
-            elif status == "error":
-                status_text = f"[red]{status}[/red]"
+                status_text = f"[green]🟢 {status}[/green]"
+            elif status == "error" or status == "failed":
+                status_text = f"[red]🔴 {status}[/red]"
+            elif status == "running":
+                status_text = f"[yellow]🔄 {status}[/yellow]"
             else:
-                status_text = status
-
-            table.add_row(
-                run.name or "-",
-                run.temporal.workflow_id if run.temporal else "N/A",
-                Padding(run.id, (0, 0, 0 if is_last_row else 1, 0)),
-                status_text,
-                start_str,
-                end_str,
+                status_text = f"❓ {status}"
+
+            console.print(
+                f"[bold cyan]{run.name or 'Unnamed Workflow'}[/bold cyan] {status_text}"
             )
+            console.print(f"  Run ID: {run.id}")
+
+            if run.temporal and run.temporal.workflow_id:
+                console.print(f"  Workflow ID: {run.temporal.workflow_id}")
+
+            console.print(f"  Started: {start_str}")
+            if end_str != "N/A":
+                console.print(f"  Completed: {end_str}")
 
-        console.print(table)
+            # Show execution time if available
+            if hasattr(run.temporal, "execution_time") and run.temporal.execution_time:
+                duration = end - start if (start and end) else None
+                if duration:
+                    console.print(f"  Duration: {duration:.2f}s")
 
     except Exception as e:
         print_error(f"Error fetching workflow runs: {str(e)}")

src/mcp_agent/cli/cloud/commands/logger/tail/main.py

@@ -17,7 +17,10 @@
 
 from mcp_agent.cli.exceptions import CLIError
 from mcp_agent.cli.auth import load_credentials, UserCredentials
-from mcp_agent.cli.cloud.commands.utils import setup_authenticated_client, resolve_server
+from mcp_agent.cli.cloud.commands.utils import (
+    setup_authenticated_client,
+    resolve_server,
+)
 from mcp_agent.cli.core.api_client import UnauthenticatedError
 from mcp_agent.cli.utils.ux import print_error
 from mcp_agent.cli.mcp_app.api_client import MCPApp, MCPAppConfiguration
@@ -135,7 +138,7 @@ def tail_logs(
 
     client = setup_authenticated_client()
     server = resolve_server(client, app_identifier)
-    
+
     try:
         if follow:
             asyncio.run(
@@ -183,7 +186,7 @@ async def _fetch_logs(
     """Fetch logs one-time via HTTP API."""
 
     # Extract app_id and config_id from the server object
-    if hasattr(server, 'appId'):  # MCPApp
+    if hasattr(server, "appId"):  # MCPApp
         app_id = server.appId
         config_id = None
     else:  # MCPAppConfiguration
@@ -264,7 +267,7 @@ async def _stream_logs(
     # Get server URL directly from the server object
     if not server.appServerInfo or not server.appServerInfo.serverUrl:
         raise CLIError("Server URL not available - server may not be deployed")
-    
+
     server_url = server.appServerInfo.serverUrl
 
     parsed = urlparse(server_url)

src/mcp_agent/cli/mcp_app/mcp_client.py

@@ -1,3 +1,4 @@
+import ast
 import asyncio
 import json
 from contextlib import asynccontextmanager
@@ -62,10 +63,13 @@ class WorkflowRunState(BaseModel):
 class WorkflowRunResult(BaseModel):
     """The result of a workflow run."""
 
+    kind: str
+    """The kind/type of result returned by the workflow run."""
+
     value: str
     """The value returned by the workflow run, if any."""
 
-    metadata: dict
+    metadata: Optional[dict[str, Any]] = None
     """Metadata associated with the workflow run result."""
 
     start_time: Optional[float] = None
@@ -99,6 +103,9 @@ class WorkflowRunTemporal(BaseModel):
     close_time: Optional[float] = None
     """The time when the workflow run completed."""
 
+    execution_time: Optional[float] = None
+    """The total time taken for the workflow run."""
+
 
 class WorkflowRun(BaseModel):
     """An execution instance of a workflow definition."""
@@ -187,9 +194,20 @@ async def list_workflow_runs(self) -> ListWorkflowRunsResult:
                 # Assuming the content is a JSON string representing a WorkflowRun item dict
                 try:
                     run_data = json.loads(item.text)
+                    if "result" in run_data and isinstance(run_data["result"], str):
+                        try:
+                            # Could be stringified python dict instead of valid JSON
+                            run_data["result"] = ast.literal_eval(run_data["result"])
+                        except (ValueError, SyntaxError) as e:
+                            try:
+                                run_data["result"] = json.loads(run_data["result"])
+                            except json.JSONDecodeError:
+                                raise ValueError(
+                                    f"Invalid workflow run result data: {e}"
+                                ) from e
                     runs.append(WorkflowRun(**run_data))
                 except json.JSONDecodeError as e:
-                    raise ValueError(f"Invalid workflow run data: {e}")
+                    raise ValueError(f"Invalid workflow run data: {e}") from e
 
         return ListWorkflowRunsResult(workflow_runs=runs)