feat: add command allowlist validation for MCP stdio transport

Add an optional allowed_commands parameter to StdioTransport that
validates the command basename against an allowlist before spawning
a subprocess. This provides defense-in-depth against configuration-
driven command injection as MCP server discovery becomes more dynamic.

- DEFAULT_ALLOWED_COMMANDS includes common runtimes: python, python3,
  node, npx, uvx, uv, deno, docker
- Validation checks os.path.basename(command) for cross-platform support
- Users can extend the allowlist, pass a custom set, or set
  allowed_commands=None to disable the check entirely
- No breaking change: all currently documented MCP server examples use
  commands in the default allowlist
- MCPServerStdio config model updated with allowed_commands field
- tool_resolver passes allowed_commands through to StdioTransport

Closes #5080

docs/en/concepts/files.mdx

@@ -134,10 +134,6 @@ result = flow.kickoff(
 )
 ```
 
-<Note type="info" title="CrewAI Platform Integration">
-When deployed on CrewAI Platform, `ImageFile`, `PDFFile`, and other file-typed fields in your flow state automatically get a file upload UI. Users can drag and drop files directly in the Platform interface. Files are stored securely and passed to agents using provider-specific optimizations (inline base64, file upload APIs, or URL references depending on the provider).
-</Note>
-
 ### With Standalone Agents
 
 Pass files directly to agent kickoff:

docs/en/concepts/flows.mdx

@@ -341,87 +341,6 @@ flow.kickoff()
 
 By providing both unstructured and structured state management options, CrewAI Flows empowers developers to build AI workflows that are both flexible and robust, catering to a wide range of application requirements.
 
-### File Inputs
-
-When using structured state, you can include file-typed fields using classes from `crewai-files`. This enables file uploads as part of your flow's input:
-
-```python
-from crewai.flow.flow import Flow, start
-from crewai_files import ImageFile, PDFFile
-from pydantic import BaseModel
-
-class OnboardingState(BaseModel):
-    document: PDFFile        # File upload
-    cover_image: ImageFile   # Image upload
-    title: str = ""          # Text input
-
-class OnboardingFlow(Flow[OnboardingState]):
-    @start()
-    def process_upload(self):
-        # Access files directly from state
-        print(f"Processing: {self.state.title}")
-        return self.state.document
-```
-
-When deployed on **CrewAI Platform**, file-typed fields automatically render as file upload dropzones in the UI. Users can drag and drop files, which are then passed to your flow.
-
-**Kicking off with files via API:**
-
-The `/kickoff` endpoint auto-detects the request format:
-- **JSON body** → normal kickoff
-- **multipart/form-data** → file upload + kickoff
-
-API users can also pass URL strings directly to file-typed fields—Pydantic coerces them automatically.
-
-### API Usage
-
-#### Option 1: Multipart kickoff (recommended)
-
-Send files directly with the kickoff request:
-
-```bash
-# With files (multipart) — same endpoint
-curl -X POST https://your-deployment.crewai.com/kickoff \
-  -H 'Authorization: Bearer YOUR_TOKEN' \
-  -F 'inputs={"company_name": "Einstein"}' \
-  -F 'cnh_image=@/path/to/document.jpg'
-```
-
-Files are automatically stored and converted to `FileInput` objects. The agent receives the file with provider-specific optimization (inline base64, file upload API, or URL reference depending on the LLM provider).
-
-#### Option 2: JSON kickoff (no files)
-
-```bash
-# Without files (JSON) — same endpoint
-curl -X POST https://your-deployment.crewai.com/kickoff \
-  -H 'Authorization: Bearer YOUR_TOKEN' \
-  -H 'Content-Type: application/json' \
-  -d '{"inputs": {"company_name": "Einstein"}}'
-```
-
-#### Option 3: Separate upload + kickoff
-
-Upload files first, then reference them:
-
-```bash
-# Step 1: Upload
-curl -X POST https://your-deployment.crewai.com/files \
-  -H 'Authorization: Bearer YOUR_TOKEN' \
-  -F 'file=@/path/to/document.jpg' \
-  -F 'field_name=cnh_image'
-# Returns: {"url": "https://...", "field_name": "cnh_image"}
-
-# Step 2: Kickoff with URL
-curl -X POST https://your-deployment.crewai.com/kickoff \
-  -H 'Authorization: Bearer YOUR_TOKEN' \
-  -H 'Content-Type: application/json' \
-  -d '{"inputs": {"company_name": "Einstein"}, "inputFiles": {"cnh_image": "https://..."}}'
-```
-
-#### On CrewAI Platform
-
-When using the Platform UI, file-typed fields automatically render as drag-and-drop upload zones. No API calls needed—just drop the file and click Run.
-
 ## Flow Persistence
 
 The @persist decorator enables automatic state persistence in CrewAI Flows, allowing you to maintain flow state across restarts or different workflow executions. This decorator can be applied at either the class level or method level, providing flexibility in how you manage state persistence.

lib/crewai/src/crewai/cli/plus_api.py

@@ -73,6 +73,7 @@ class PlusAPI:
         description: str | None,
         encoded_file: str,
         available_exports: list[dict[str, Any]] | None = None,
+        tools_metadata: list[dict[str, Any]] | None = None,
     ) -> httpx.Response:
         params = {
             "handle": handle,
@@ -81,6 +82,9 @@ class PlusAPI:
             "file": encoded_file,
             "description": description,
             "available_exports": available_exports,
+            "tools_metadata": {"package": handle, "tools": tools_metadata}
+            if tools_metadata is not None
+            else None,
         }
         return self._make_request("POST", f"{self.TOOLS_RESOURCE}", json=params)
 

lib/crewai/src/crewai/cli/tools/main.py

@@ -17,6 +17,7 @@ from crewai.cli.constants import DEFAULT_CREWAI_ENTERPRISE_URL
 from crewai.cli.utils import (
     build_env_with_tool_repository_credentials,
     extract_available_exports,
+    extract_tools_metadata,
     get_project_description,
     get_project_name,
     get_project_version,
@@ -101,6 +102,18 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
             console.print(
                 f"[green]Found these tools to publish: {', '.join([e['name'] for e in available_exports])}[/green]"
             )
+
+        console.print("[bold blue]Extracting tool metadata...[/bold blue]")
+        try:
+            tools_metadata = extract_tools_metadata()
+        except Exception as e:
+            console.print(
+                f"[yellow]Warning: Could not extract tool metadata: {e}[/yellow]\n"
+                f"Publishing will continue without detailed metadata."
+            )
+            tools_metadata = []
+
+        self._print_tools_preview(tools_metadata)
         self._print_current_organization()
 
         with tempfile.TemporaryDirectory() as temp_build_dir:
@@ -118,7 +131,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
                     "Project build failed. Please ensure that the command `uv build --sdist` completes successfully.",
                     style="bold red",
                 )
-                raise SystemExit
+                raise SystemExit(1)
 
             tarball_path = os.path.join(temp_build_dir, tarball_filename)
             with open(tarball_path, "rb") as file:
@@ -134,6 +147,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
             description=project_description,
             encoded_file=f"data:application/x-gzip;base64,{encoded_tarball}",
             available_exports=available_exports,
+            tools_metadata=tools_metadata,
         )
 
         self._validate_response(publish_response)
@@ -246,6 +260,55 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
             )
             raise SystemExit
 
+    def _print_tools_preview(self, tools_metadata: list[dict[str, Any]]) -> None:
+        if not tools_metadata:
+            console.print("[yellow]No tool metadata extracted.[/yellow]")
+            return
+
+        console.print(
+            f"\n[bold]Tools to be published ({len(tools_metadata)}):[/bold]\n"
+        )
+
+        for tool in tools_metadata:
+            console.print(f"  [bold cyan]{tool.get('name', 'Unknown')}[/bold cyan]")
+            if tool.get("module"):
+                console.print(f"    Module: {tool.get('module')}")
+            console.print(f"    Name: {tool.get('humanized_name', 'N/A')}")
+            console.print(
+                f"    Description: {tool.get('description', 'N/A')[:80]}{'...' if len(tool.get('description', '')) > 80 else ''}"
+            )
+
+            init_params = tool.get("init_params_schema", {}).get("properties", {})
+            if init_params:
+                required = tool.get("init_params_schema", {}).get("required", [])
+                console.print("    Init parameters:")
+                for param_name, param_info in init_params.items():
+                    param_type = param_info.get("type", "any")
+                    is_required = param_name in required
+                    req_marker = "[red]*[/red]" if is_required else ""
+                    default = (
+                        f" = {param_info['default']}" if "default" in param_info else ""
+                    )
+                    console.print(
+                        f"      - {param_name}: {param_type}{default} {req_marker}"
+                    )
+
+            env_vars = tool.get("env_vars", [])
+            if env_vars:
+                console.print("    Environment variables:")
+                for env_var in env_vars:
+                    req_marker = "[red]*[/red]" if env_var.get("required") else ""
+                    default = (
+                        f" (default: {env_var['default']})"
+                        if env_var.get("default")
+                        else ""
+                    )
+                    console.print(
+                        f"      - {env_var['name']}: {env_var.get('description', 'N/A')}{default} {req_marker}"
+                    )
+
+            console.print()
+
     def _print_current_organization(self) -> None:
         settings = Settings()
         if settings.org_uuid:

lib/crewai/src/crewai/cli/utils.py

@@ -1,10 +1,15 @@
-from functools import reduce
+from collections.abc import Generator, Mapping
+from contextlib import contextmanager
+from functools import lru_cache, reduce
+import hashlib
 import importlib.util
+import inspect
 from inspect import getmro, isclass, isfunction, ismethod
 import os
 from pathlib import Path
 import shutil
 import sys
+import types
 from typing import Any, cast, get_type_hints
 
 import click
@@ -544,43 +549,62 @@ def build_env_with_tool_repository_credentials(
     return env
 
 
+@contextmanager
+def _load_module_from_file(
+    init_file: Path, module_name: str | None = None
+) -> Generator[types.ModuleType | None, None, None]:
+    """
+    Context manager for loading a module from file with automatic cleanup.
+
+    Yields the loaded module or None if loading fails.
+    """
+    if module_name is None:
+        module_name = (
+            f"temp_module_{hashlib.sha256(str(init_file).encode()).hexdigest()[:8]}"
+        )
+
+    spec = importlib.util.spec_from_file_location(module_name, init_file)
+    if not spec or not spec.loader:
+        yield None
+        return
+
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[module_name] = module
+
+    try:
+        spec.loader.exec_module(module)
+        yield module
+    finally:
+        sys.modules.pop(module_name, None)
+
+
 def _load_tools_from_init(init_file: Path) -> list[dict[str, Any]]:
     """
     Load and validate tools from a given __init__.py file.
     """
-    spec = importlib.util.spec_from_file_location("temp_module", init_file)
-
-    if not spec or not spec.loader:
-        return []
-
-    module = importlib.util.module_from_spec(spec)
-    sys.modules["temp_module"] = module
-
     try:
-        spec.loader.exec_module(module)
+        with _load_module_from_file(init_file) as module:
+            if module is None:
+                return []
 
-        if not hasattr(module, "__all__"):
-            console.print(
-                f"Warning: No __all__ defined in {init_file}",
-                style="bold yellow",
-            )
-            raise SystemExit(1)
-
-        return [
-            {
-                "name": name,
-            }
-            for name in module.__all__
-            if hasattr(module, name) and is_valid_tool(getattr(module, name))
-        ]
+            if not hasattr(module, "__all__"):
+                console.print(
+                    f"Warning: No __all__ defined in {init_file}",
+                    style="bold yellow",
+                )
+                raise SystemExit(1)
 
+            return [
+                {"name": name}
+                for name in module.__all__
+                if hasattr(module, name) and is_valid_tool(getattr(module, name))
+            ]
+    except SystemExit:
+        raise
     except Exception as e:
         console.print(f"[red]Warning: Could not load {init_file}: {e!s}[/red]")
         raise SystemExit(1) from e
 
-    finally:
-        sys.modules.pop("temp_module", None)
-
 
 def _print_no_tools_warning() -> None:
     """
@@ -610,3 +634,242 @@ def _print_no_tools_warning() -> None:
         "    # ... implementation\n"
         "    return result\n"
     )
+
+
+def extract_tools_metadata(dir_path: str = "src") -> list[dict[str, Any]]:
+    """
+    Extract rich metadata from tool classes in the project.
+
+    Returns a list of tool metadata dictionaries containing:
+    - name: Class name
+    - humanized_name: From name field default
+    - description: From description field default
+    - run_params_schema: JSON Schema for _run() params (from args_schema)
+    - init_params_schema: JSON Schema for __init__ params (filtered)
+    - env_vars: List of environment variable dicts
+    """
+    tools_metadata: list[dict[str, Any]] = []
+
+    for init_file in Path(dir_path).glob("**/__init__.py"):
+        tools = _extract_tool_metadata_from_init(init_file)
+        tools_metadata.extend(tools)
+
+    return tools_metadata
+
+
+def _extract_tool_metadata_from_init(init_file: Path) -> list[dict[str, Any]]:
+    """
+    Load module from init file and extract metadata from valid tool classes.
+    """
+    from crewai.tools.base_tool import BaseTool
+
+    try:
+        with _load_module_from_file(init_file) as module:
+            if module is None:
+                return []
+
+            exported_names = getattr(module, "__all__", None)
+            if not exported_names:
+                return []
+
+            tools_metadata = []
+            for name in exported_names:
+                obj = getattr(module, name, None)
+                if obj is None or not (
+                    inspect.isclass(obj) and issubclass(obj, BaseTool)
+                ):
+                    continue
+                if tool_info := _extract_single_tool_metadata(obj):
+                    tools_metadata.append(tool_info)
+
+            return tools_metadata
+    except Exception as e:
+        console.print(
+            f"[yellow]Warning: Could not extract metadata from {init_file}: {e}[/yellow]"
+        )
+        return []
+
+
+def _extract_single_tool_metadata(tool_class: type) -> dict[str, Any] | None:
+    """
+    Extract metadata from a single tool class.
+    """
+    try:
+        core_schema = cast(Any, tool_class).__pydantic_core_schema__
+        if not core_schema:
+            return None
+
+        schema = _unwrap_schema(core_schema)
+        fields = schema.get("schema", {}).get("fields", {})
+
+        try:
+            file_path = inspect.getfile(tool_class)
+            relative_path = Path(file_path).relative_to(Path.cwd())
+            module_path = relative_path.with_suffix("")
+            if module_path.parts[0] == "src":
+                module_path = Path(*module_path.parts[1:])
+            if module_path.name == "__init__":
+                module_path = module_path.parent
+            module = ".".join(module_path.parts)
+        except (TypeError, ValueError):
+            module = tool_class.__module__
+
+        return {
+            "name": tool_class.__name__,
+            "module": module,
+            "humanized_name": _extract_field_default(
+                fields.get("name"), fallback=tool_class.__name__
+            ),
+            "description": str(
+                _extract_field_default(fields.get("description"))
+            ).strip(),
+            "run_params_schema": _extract_run_params_schema(fields.get("args_schema")),
+            "init_params_schema": _extract_init_params_schema(tool_class),
+            "env_vars": _extract_env_vars(fields.get("env_vars")),
+        }
+
+    except Exception:
+        return None
+
+
+def _unwrap_schema(schema: Mapping[str, Any] | dict[str, Any]) -> dict[str, Any]:
+    """
+    Unwrap nested schema structures to get to the actual schema definition.
+    """
+    result: dict[str, Any] = dict(schema)
+    while (
+        result.get("type")
+        in {"function-after", "function-before", "function-wrap", "default"}
+        and "schema" in result
+    ):
+        result = dict(result["schema"])
+    if result.get("type") == "definitions" and "schema" in result:
+        result = dict(result["schema"])
+    return result
+
+
+def _extract_field_default(
+    field: dict[str, Any] | None, fallback: str | list[Any] = ""
+) -> str | list[Any] | int:
+    """
+    Extract the default value from a field schema.
+    """
+    if not field:
+        return fallback
+
+    schema = field.get("schema", {})
+    default = schema.get("default")
+    return default if isinstance(default, (list, str, int)) else fallback
+
+
+@lru_cache(maxsize=1)
+def _get_schema_generator() -> type:
+    """Get a SchemaGenerator that omits non-serializable defaults."""
+    from pydantic.json_schema import GenerateJsonSchema
+    from pydantic_core import PydanticOmit
+
+    class SchemaGenerator(GenerateJsonSchema):
+        def handle_invalid_for_json_schema(
+            self, schema: Any, error_info: Any
+        ) -> dict[str, Any]:
+            raise PydanticOmit
+
+    return SchemaGenerator
+
+
+def _extract_run_params_schema(
+    args_schema_field: dict[str, Any] | None,
+) -> dict[str, Any]:
+    """
+    Extract JSON Schema for the tool's run parameters from args_schema field.
+    """
+    from pydantic import BaseModel
+
+    if not args_schema_field:
+        return {}
+
+    args_schema_class = args_schema_field.get("schema", {}).get("default")
+    if not (
+        inspect.isclass(args_schema_class) and issubclass(args_schema_class, BaseModel)
+    ):
+        return {}
+
+    try:
+        return args_schema_class.model_json_schema(
+            schema_generator=_get_schema_generator()
+        )
+    except Exception:
+        return {}
+
+
+_IGNORED_INIT_PARAMS = frozenset(
+    {
+        "name",
+        "description",
+        "env_vars",
+        "args_schema",
+        "description_updated",
+        "cache_function",
+        "result_as_answer",
+        "max_usage_count",
+        "current_usage_count",
+        "package_dependencies",
+    }
+)
+
+
+def _extract_init_params_schema(tool_class: type) -> dict[str, Any]:
+    """
+    Extract JSON Schema for the tool's __init__ parameters, filtering out base fields.
+    """
+    try:
+        json_schema: dict[str, Any] = cast(Any, tool_class).model_json_schema(
+            schema_generator=_get_schema_generator(), mode="serialization"
+        )
+        filtered_properties = {
+            key: value
+            for key, value in json_schema.get("properties", {}).items()
+            if key not in _IGNORED_INIT_PARAMS
+        }
+        json_schema["properties"] = filtered_properties
+        if "required" in json_schema:
+            json_schema["required"] = [
+                key for key in json_schema["required"] if key in filtered_properties
+            ]
+        return json_schema
+    except Exception:
+        return {}
+
+
+def _extract_env_vars(env_vars_field: dict[str, Any] | None) -> list[dict[str, Any]]:
+    """
+    Extract environment variable definitions from env_vars field.
+    """
+    from crewai.tools.base_tool import EnvVar
+
+    if not env_vars_field:
+        return []
+
+    schema = env_vars_field.get("schema", {})
+    default = schema.get("default")
+    if default is None:
+        default_factory = schema.get("default_factory")
+        if callable(default_factory):
+            try:
+                default = default_factory()
+            except Exception:
+                default = []
+
+    if not isinstance(default, list):
+        return []
+
+    return [
+        {
+            "name": env_var.name,
+            "description": env_var.description,
+            "required": env_var.required,
+            "default": env_var.default,
+        }
+        for env_var in default
+        if isinstance(env_var, EnvVar)
+    ]

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -1966,37 +1966,6 @@ class AgentExecutor(Flow[AgentExecutorState], CrewAgentExecutorMixin):
             "original_tool": original_tool,
         }
 
-    def _extract_tool_name(self, tool_call: Any) -> str:
-        """Extract tool name from various tool call formats."""
-        if hasattr(tool_call, "function"):
-            return sanitize_tool_name(tool_call.function.name)
-        if hasattr(tool_call, "function_call") and tool_call.function_call:
-            return sanitize_tool_name(tool_call.function_call.name)
-        if hasattr(tool_call, "name"):
-            return sanitize_tool_name(tool_call.name)
-        if isinstance(tool_call, dict):
-            func_info = tool_call.get("function", {})
-            return sanitize_tool_name(
-                func_info.get("name", "") or tool_call.get("name", "unknown")
-            )
-        return "unknown"
-
-    @router(execute_native_tool)
-    def check_native_todo_completion(
-        self,
-    ) -> Literal["todo_satisfied", "todo_not_satisfied"]:
-        """Check if the native tool execution satisfied the active todo.
-
-        Similar to check_todo_completion but for native tool execution path.
-        """
-        current_todo = self.state.todos.current_todo
-
-        if not current_todo:
-            return "todo_not_satisfied"
-
-        # For native tools, any tool execution satisfies the todo
-        return "todo_satisfied"
-
     @listen("initialized")
     def continue_iteration(self) -> Literal["check_iteration"]:
         """Bridge listener that connects iteration loop back to iteration check."""

lib/crewai/src/crewai/llm.py

@@ -753,7 +753,7 @@ class LLM(BaseLLM):
             "temperature": self.temperature,
             "top_p": self.top_p,
             "n": self.n,
-            "stop": self.stop or None,
+            "stop": (self.stop or None) if self.supports_stop_words() else None,
             "max_tokens": self.max_tokens or self.max_completion_tokens,
             "presence_penalty": self.presence_penalty,
             "frequency_penalty": self.frequency_penalty,
@@ -1825,9 +1825,11 @@ class LLM(BaseLLM):
                     # whether to summarize the content or abort based on the respect_context_window flag
                     raise
                 except Exception as e:
-                    unsupported_stop = "Unsupported parameter" in str(
-                        e
-                    ) and "'stop'" in str(e)
+                    error_str = str(e)
+                    unsupported_stop = "'stop'" in error_str and (
+                        "Unsupported parameter" in error_str
+                        or "does not support parameters" in error_str
+                    )
 
                     if unsupported_stop:
                         if (
@@ -1961,9 +1963,11 @@ class LLM(BaseLLM):
                 except LLMContextLengthExceededError:
                     raise
                 except Exception as e:
-                    unsupported_stop = "Unsupported parameter" in str(
-                        e
-                    ) and "'stop'" in str(e)
+                    error_str = str(e)
+                    unsupported_stop = "'stop'" in error_str and (
+                        "Unsupported parameter" in error_str
+                        or "does not support parameters" in error_str
+                    )
 
                     if unsupported_stop:
                         if (
@@ -2263,6 +2267,10 @@ class LLM(BaseLLM):
         Note: This method is only used by the litellm fallback path.
         Native providers override this method with their own implementation.
         """
+        model_lower = self.model.lower() if self.model else ""
+        if "gpt-5" in model_lower:
+            return False
+
         if not LITELLM_AVAILABLE or get_supported_openai_params is None:
             # When litellm is not available, assume stop words are supported
             return True

lib/crewai/src/crewai/llms/providers/openai/completion.py

@@ -2245,6 +2245,9 @@ class OpenAICompletion(BaseLLM):
 
     def supports_stop_words(self) -> bool:
         """Check if the model supports stop words."""
+        model_lower = self.model.lower() if self.model else ""
+        if "gpt-5" in model_lower:
+            return False
         return not self.is_o1_model
 
     def get_context_window_size(self) -> int:

lib/crewai/src/crewai/mcp/config.py

@@ -7,6 +7,7 @@ various transport types, similar to OpenAI's Agents SDK.
 from pydantic import BaseModel, Field
 
 from crewai.mcp.filters import ToolFilter
+from crewai.mcp.transports.stdio import DEFAULT_ALLOWED_COMMANDS
 
 
 class MCPServerStdio(BaseModel):
@@ -44,6 +45,14 @@ class MCPServerStdio(BaseModel):
         default=None,
         description="Optional tool filter for filtering available tools.",
     )
+    allowed_commands: frozenset[str] | None = Field(
+        default=DEFAULT_ALLOWED_COMMANDS,
+        description=(
+            "Optional frozenset of allowed command basenames for security validation. "
+            "Defaults to common runtimes (python, node, npx, uvx, uv, deno, docker). "
+            "Set to None to disable the allowlist check."
+        ),
+    )
     cache_tools_list: bool = Field(
         default=False,
         description="Whether to cache the tool list for faster subsequent access.",

lib/crewai/src/crewai/mcp/tool_resolver.py

@@ -292,6 +292,7 @@ class MCPToolResolver:
                 command=mcp_config.command,
                 args=mcp_config.args,
                 env=mcp_config.env,
+                allowed_commands=mcp_config.allowed_commands,
             )
             server_name = f"{mcp_config.command}_{'_'.join(mcp_config.args)}"
         elif isinstance(mcp_config, MCPServerHTTP):

lib/crewai/src/crewai/mcp/transports/__init__.py

@@ -3,11 +3,12 @@
 from crewai.mcp.transports.base import BaseTransport, TransportType
 from crewai.mcp.transports.http import HTTPTransport
 from crewai.mcp.transports.sse import SSETransport
-from crewai.mcp.transports.stdio import StdioTransport
+from crewai.mcp.transports.stdio import DEFAULT_ALLOWED_COMMANDS, StdioTransport
 
 
 __all__ = [
     "BaseTransport",
+    "DEFAULT_ALLOWED_COMMANDS",
     "HTTPTransport",
     "SSETransport",
     "StdioTransport",

lib/crewai/src/crewai/mcp/transports/stdio.py

@@ -9,6 +9,22 @@ from typing_extensions import Self
 
 from crewai.mcp.transports.base import BaseTransport, TransportType
 
+# Default allowlist for common MCP server runtimes.
+# Covers the vast majority of MCP server launch commands.
+# Pass ``allowed_commands=None`` to disable validation entirely.
+DEFAULT_ALLOWED_COMMANDS: frozenset[str] = frozenset(
+    {
+        "python",
+        "python3",
+        "node",
+        "npx",
+        "uvx",
+        "uv",
+        "deno",
+        "docker",
+    }
+)
+
 
 class StdioTransport(BaseTransport):
     """Stdio transport for connecting to local MCP servers.
@@ -34,6 +50,7 @@ class StdioTransport(BaseTransport):
         command: str,
         args: list[str] | None = None,
         env: dict[str, str] | None = None,
+        allowed_commands: frozenset[str] | None = DEFAULT_ALLOWED_COMMANDS,
         **kwargs: Any,
     ) -> None:
         """Initialize stdio transport.
@@ -42,9 +59,24 @@ class StdioTransport(BaseTransport):
             command: Command to execute (e.g., "python", "node", "npx").
             args: Command arguments (e.g., ["server.py"] or ["-y", "@mcp/server"]).
             env: Environment variables to pass to the process.
+            allowed_commands: Optional frozenset of allowed command basenames.
+                Defaults to ``DEFAULT_ALLOWED_COMMANDS`` which includes common
+                runtimes (python, node, npx, uvx, uv, deno, docker).  Pass
+                ``None`` to disable the check entirely.
             **kwargs: Additional transport options.
         """
         super().__init__(**kwargs)
+
+        if allowed_commands is not None:
+            base_command = os.path.basename(command)
+            if base_command not in allowed_commands:
+                raise ValueError(
+                    f"Command '{command}' is not in the allowed commands list: "
+                    f"{sorted(allowed_commands)}. "
+                    f"To allow this command, add it to allowed_commands or pass "
+                    f"allowed_commands=None to disable this check."
+                )
+
         self.command = command
         self.args = args or []
         self.env = env or {}

lib/crewai/tests/agents/test_agent_executor.py

@@ -879,30 +879,6 @@ class TestNativeToolExecution:
         assert len(tool_messages) == 1
         assert tool_messages[0]["tool_call_id"] == "call_1"
 
-    def test_check_native_todo_completion_requires_current_todo(
-        self, mock_dependencies
-    ):
-        from crewai.utilities.planning_types import TodoList
-
-        executor = AgentExecutor(**mock_dependencies)
-
-        # No current todo → not satisfied
-        executor.state.todos = TodoList(items=[])
-        assert executor.check_native_todo_completion() == "todo_not_satisfied"
-
-        # With a current todo that has tool_to_use → satisfied
-        running = TodoItem(
-            step_number=1,
-            description="Use the expected tool",
-            tool_to_use="expected_tool",
-            status="running",
-        )
-        executor.state.todos = TodoList(items=[running])
-        assert executor.check_native_todo_completion() == "todo_satisfied"
-
-        # With a current todo without tool_to_use → still satisfied
-        running.tool_to_use = None
-        assert executor.check_native_todo_completion() == "todo_satisfied"
 
 
 class TestPlannerObserver:

lib/crewai/tests/cassettes/test_litellm_gpt5_call_succeeds_without_stop_error.yaml

@@ -0,0 +1,110 @@
+interactions:
+- request:
+    body: '{"messages":[{"role":"user","content":"What is the capital of France?"}],"model":"gpt-5"}'
+    headers:
+      User-Agent:
+      - X-USER-AGENT-XXX
+      accept:
+      - application/json
+      accept-encoding:
+      - ACCEPT-ENCODING-XXX
+      authorization:
+      - AUTHORIZATION-XXX
+      connection:
+      - keep-alive
+      content-length:
+      - '89'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      x-stainless-arch:
+      - X-STAINLESS-ARCH-XXX
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - X-STAINLESS-OS-XXX
+      x-stainless-package-version:
+      - 1.83.0
+      x-stainless-raw-response:
+      - 'true'
+      x-stainless-read-timeout:
+      - X-STAINLESS-READ-TIMEOUT-XXX
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.13.2
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    body:
+      string: "{\n  \"id\": \"chatcmpl-DO4LcSpy72yIXCYSIVOQEXWNXydgn\",\n  \"object\":
+        \"chat.completion\",\n  \"created\": 1774628956,\n  \"model\": \"gpt-5-2025-08-07\",\n
+        \ \"choices\": [\n    {\n      \"index\": 0,\n      \"message\": {\n        \"role\":
+        \"assistant\",\n        \"content\": \"Paris.\",\n        \"refusal\": null,\n
+        \       \"annotations\": []\n      },\n      \"finish_reason\": \"stop\"\n
+        \   }\n  ],\n  \"usage\": {\n    \"prompt_tokens\": 13,\n    \"completion_tokens\":
+        11,\n    \"total_tokens\": 24,\n    \"prompt_tokens_details\": {\n      \"cached_tokens\":
+        0,\n      \"audio_tokens\": 0\n    },\n    \"completion_tokens_details\":
+        {\n      \"reasoning_tokens\": 0,\n      \"audio_tokens\": 0,\n      \"accepted_prediction_tokens\":
+        0,\n      \"rejected_prediction_tokens\": 0\n    }\n  },\n  \"service_tier\":
+        \"default\",\n  \"system_fingerprint\": null\n}\n"
+    headers:
+      CF-Cache-Status:
+      - DYNAMIC
+      CF-Ray:
+      - 9e2fc5dce85582fb-GIG
+      Connection:
+      - keep-alive
+      Content-Type:
+      - application/json
+      Date:
+      - Fri, 27 Mar 2026 16:29:17 GMT
+      Server:
+      - cloudflare
+      Strict-Transport-Security:
+      - STS-XXX
+      Transfer-Encoding:
+      - chunked
+      X-Content-Type-Options:
+      - X-CONTENT-TYPE-XXX
+      access-control-expose-headers:
+      - ACCESS-CONTROL-XXX
+      alt-svc:
+      - h3=":443"; ma=86400
+      content-length:
+      - '772'
+      openai-organization:
+      - OPENAI-ORG-XXX
+      openai-processing-ms:
+      - '1343'
+      openai-project:
+      - OPENAI-PROJECT-XXX
+      openai-version:
+      - '2020-10-01'
+      set-cookie:
+      - SET-COOKIE-XXX
+      x-openai-proxy-wasm:
+      - v0.1
+      x-ratelimit-limit-requests:
+      - X-RATELIMIT-LIMIT-REQUESTS-XXX
+      x-ratelimit-limit-tokens:
+      - X-RATELIMIT-LIMIT-TOKENS-XXX
+      x-ratelimit-remaining-requests:
+      - X-RATELIMIT-REMAINING-REQUESTS-XXX
+      x-ratelimit-remaining-tokens:
+      - X-RATELIMIT-REMAINING-TOKENS-XXX
+      x-ratelimit-reset-requests:
+      - X-RATELIMIT-RESET-REQUESTS-XXX
+      x-ratelimit-reset-tokens:
+      - X-RATELIMIT-RESET-TOKENS-XXX
+      x-request-id:
+      - X-REQUEST-ID-XXX
+    status:
+      code: 200
+      message: OK
+version: 1

lib/crewai/tests/cli/test_plus_api.py

@@ -136,6 +136,7 @@ class TestPlusAPI(unittest.TestCase):
             "file": encoded_file,
             "description": description,
             "available_exports": None,
+            "tools_metadata": None,
         }
         mock_make_request.assert_called_once_with(
             "POST", "/crewai_plus/api/v1/tools", json=params
@@ -173,6 +174,7 @@ class TestPlusAPI(unittest.TestCase):
             "file": encoded_file,
             "description": description,
             "available_exports": None,
+            "tools_metadata": None,
         }
 
         self.assert_request_with_org_id(
@@ -201,6 +203,48 @@ class TestPlusAPI(unittest.TestCase):
             "file": encoded_file,
             "description": description,
             "available_exports": None,
+            "tools_metadata": None,
+        }
+        mock_make_request.assert_called_once_with(
+            "POST", "/crewai_plus/api/v1/tools", json=params
+        )
+        self.assertEqual(response, mock_response)
+
+    @patch("crewai.cli.plus_api.PlusAPI._make_request")
+    def test_publish_tool_with_tools_metadata(self, mock_make_request):
+        mock_response = MagicMock()
+        mock_make_request.return_value = mock_response
+        handle = "test_tool_handle"
+        public = True
+        version = "1.0.0"
+        description = "Test tool description"
+        encoded_file = "encoded_test_file"
+        available_exports = [{"name": "MyTool"}]
+        tools_metadata = [
+            {
+                "name": "MyTool",
+                "humanized_name": "my_tool",
+                "description": "A test tool",
+                "run_params_schema": {"type": "object", "properties": {}},
+                "init_params_schema": {"type": "object", "properties": {}},
+                "env_vars": [{"name": "API_KEY", "description": "API key", "required": True, "default": None}],
+            }
+        ]
+
+        response = self.api.publish_tool(
+            handle, public, version, description, encoded_file,
+            available_exports=available_exports,
+            tools_metadata=tools_metadata,
+        )
+
+        params = {
+            "handle": handle,
+            "public": public,
+            "version": version,
+            "file": encoded_file,
+            "description": description,
+            "available_exports": available_exports,
+            "tools_metadata": {"package": handle, "tools": tools_metadata},
         }
         mock_make_request.assert_called_once_with(
             "POST", "/crewai_plus/api/v1/tools", json=params

lib/crewai/tests/cli/test_utils.py

@@ -363,3 +363,290 @@ def test_get_crews_ignores_template_directories(
     utils.get_crews()
 
     assert not template_crew_detected
+
+
+# Tests for extract_tools_metadata
+
+
+def test_extract_tools_metadata_empty_project(temp_project_dir):
+    """Test that extract_tools_metadata returns empty list for empty project."""
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert metadata == []
+
+
+def test_extract_tools_metadata_no_init_file(temp_project_dir):
+    """Test that extract_tools_metadata returns empty list when no __init__.py exists."""
+    (temp_project_dir / "some_file.py").write_text("print('hello')")
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert metadata == []
+
+
+def test_extract_tools_metadata_empty_init_file(temp_project_dir):
+    """Test that extract_tools_metadata returns empty list for empty __init__.py."""
+    create_init_file(temp_project_dir, "")
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert metadata == []
+
+
+def test_extract_tools_metadata_no_all_variable(temp_project_dir):
+    """Test that extract_tools_metadata returns empty list when __all__ is not defined."""
+    create_init_file(
+        temp_project_dir,
+        "from crewai.tools import BaseTool\n\nclass MyTool(BaseTool):\n    pass",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert metadata == []
+
+
+def test_extract_tools_metadata_valid_base_tool_class(temp_project_dir):
+    """Test that extract_tools_metadata extracts metadata from a valid BaseTool class."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+
+class MyTool(BaseTool):
+    name: str = "my_tool"
+    description: str = "A test tool"
+
+__all__ = ['MyTool']
+""",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 1
+    assert metadata[0]["name"] == "MyTool"
+    assert metadata[0]["humanized_name"] == "my_tool"
+    assert metadata[0]["description"] == "A test tool"
+
+
+def test_extract_tools_metadata_with_args_schema(temp_project_dir):
+    """Test that extract_tools_metadata extracts run_params_schema from args_schema."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+from pydantic import BaseModel
+
+class MyToolInput(BaseModel):
+    query: str
+    limit: int = 10
+
+class MyTool(BaseTool):
+    name: str = "my_tool"
+    description: str = "A test tool"
+    args_schema: type[BaseModel] = MyToolInput
+
+__all__ = ['MyTool']
+""",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 1
+    assert metadata[0]["name"] == "MyTool"
+    run_params = metadata[0]["run_params_schema"]
+    assert "properties" in run_params
+    assert "query" in run_params["properties"]
+    assert "limit" in run_params["properties"]
+
+
+def test_extract_tools_metadata_with_env_vars(temp_project_dir):
+    """Test that extract_tools_metadata extracts env_vars."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+from crewai.tools.base_tool import EnvVar
+
+class MyTool(BaseTool):
+    name: str = "my_tool"
+    description: str = "A test tool"
+    env_vars: list[EnvVar] = [
+        EnvVar(name="MY_API_KEY", description="API key for service", required=True),
+        EnvVar(name="MY_OPTIONAL_VAR", description="Optional var", required=False, default="default_value"),
+    ]
+
+__all__ = ['MyTool']
+""",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 1
+    env_vars = metadata[0]["env_vars"]
+    assert len(env_vars) == 2
+    assert env_vars[0]["name"] == "MY_API_KEY"
+    assert env_vars[0]["description"] == "API key for service"
+    assert env_vars[0]["required"] is True
+    assert env_vars[1]["name"] == "MY_OPTIONAL_VAR"
+    assert env_vars[1]["required"] is False
+    assert env_vars[1]["default"] == "default_value"
+
+
+def test_extract_tools_metadata_with_env_vars_field_default_factory(temp_project_dir):
+    """Test that extract_tools_metadata extracts env_vars declared with Field(default_factory=...)."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+from crewai.tools.base_tool import EnvVar
+from pydantic import Field
+
+class MyTool(BaseTool):
+    name: str = "my_tool"
+    description: str = "A test tool"
+    env_vars: list[EnvVar] = Field(
+        default_factory=lambda: [
+            EnvVar(name="MY_TOOL_API", description="API token for my tool", required=True),
+        ]
+    )
+
+__all__ = ['MyTool']
+""",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 1
+    env_vars = metadata[0]["env_vars"]
+    assert len(env_vars) == 1
+    assert env_vars[0]["name"] == "MY_TOOL_API"
+    assert env_vars[0]["description"] == "API token for my tool"
+    assert env_vars[0]["required"] is True
+
+
+def test_extract_tools_metadata_with_custom_init_params(temp_project_dir):
+    """Test that extract_tools_metadata extracts init_params_schema with custom params."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+
+class MyTool(BaseTool):
+    name: str = "my_tool"
+    description: str = "A test tool"
+    api_endpoint: str = "https://api.example.com"
+    timeout: int = 30
+
+__all__ = ['MyTool']
+""",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 1
+    init_params = metadata[0]["init_params_schema"]
+    assert "properties" in init_params
+    # Custom params should be included
+    assert "api_endpoint" in init_params["properties"]
+    assert "timeout" in init_params["properties"]
+    # Base params should be filtered out
+    assert "name" not in init_params["properties"]
+    assert "description" not in init_params["properties"]
+
+
+def test_extract_tools_metadata_multiple_tools(temp_project_dir):
+    """Test that extract_tools_metadata extracts metadata from multiple tools."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+
+class FirstTool(BaseTool):
+    name: str = "first_tool"
+    description: str = "First test tool"
+
+class SecondTool(BaseTool):
+    name: str = "second_tool"
+    description: str = "Second test tool"
+
+__all__ = ['FirstTool', 'SecondTool']
+""",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 2
+    names = [m["name"] for m in metadata]
+    assert "FirstTool" in names
+    assert "SecondTool" in names
+
+
+def test_extract_tools_metadata_multiple_init_files(temp_project_dir):
+    """Test that extract_tools_metadata extracts metadata from multiple __init__.py files."""
+    # Create tool in root __init__.py
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+
+class RootTool(BaseTool):
+    name: str = "root_tool"
+    description: str = "Root tool"
+
+__all__ = ['RootTool']
+""",
+    )
+
+    # Create nested package with another tool
+    nested_dir = temp_project_dir / "nested"
+    nested_dir.mkdir()
+    create_init_file(
+        nested_dir,
+        """from crewai.tools import BaseTool
+
+class NestedTool(BaseTool):
+    name: str = "nested_tool"
+    description: str = "Nested tool"
+
+__all__ = ['NestedTool']
+""",
+    )
+
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 2
+    names = [m["name"] for m in metadata]
+    assert "RootTool" in names
+    assert "NestedTool" in names
+
+
+def test_extract_tools_metadata_ignores_non_tool_exports(temp_project_dir):
+    """Test that extract_tools_metadata ignores non-BaseTool exports."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+
+class MyTool(BaseTool):
+    name: str = "my_tool"
+    description: str = "A test tool"
+
+def not_a_tool():
+    pass
+
+SOME_CONSTANT = "value"
+
+__all__ = ['MyTool', 'not_a_tool', 'SOME_CONSTANT']
+""",
+    )
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert len(metadata) == 1
+    assert metadata[0]["name"] == "MyTool"
+
+
+def test_extract_tools_metadata_import_error_returns_empty(temp_project_dir):
+    """Test that extract_tools_metadata returns empty list on import error."""
+    create_init_file(
+        temp_project_dir,
+        """from nonexistent_module import something
+
+class MyTool(BaseTool):
+    pass
+
+__all__ = ['MyTool']
+""",
+    )
+    # Should not raise, just return empty list
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert metadata == []
+
+
+def test_extract_tools_metadata_syntax_error_returns_empty(temp_project_dir):
+    """Test that extract_tools_metadata returns empty list on syntax error."""
+    create_init_file(
+        temp_project_dir,
+        """from crewai.tools import BaseTool
+
+class MyTool(BaseTool):
+    # Missing closing parenthesis
+    def __init__(self, name:
+        pass
+
+__all__ = ['MyTool']
+""",
+    )
+    # Should not raise, just return empty list
+    metadata = utils.extract_tools_metadata(dir_path=str(temp_project_dir))
+    assert metadata == []

lib/crewai/tests/cli/tools/test_main.py

@@ -185,9 +185,14 @@ def test_publish_when_not_in_sync(mock_is_synced, capsys, tool_command):
     "crewai.cli.tools.main.extract_available_exports",
     return_value=[{"name": "SampleTool"}],
 )
+@patch(
+    "crewai.cli.tools.main.extract_tools_metadata",
+    return_value=[{"name": "SampleTool", "humanized_name": "sample_tool", "description": "A sample tool", "run_params_schema": {}, "init_params_schema": {}, "env_vars": []}],
+)
 @patch("crewai.cli.tools.main.ToolCommand._print_current_organization")
 def test_publish_when_not_in_sync_and_force(
     mock_print_org,
+    mock_tools_metadata,
     mock_available_exports,
     mock_is_synced,
     mock_publish,
@@ -222,6 +227,7 @@ def test_publish_when_not_in_sync_and_force(
         description="A sample tool",
         encoded_file=unittest.mock.ANY,
         available_exports=[{"name": "SampleTool"}],
+        tools_metadata=[{"name": "SampleTool", "humanized_name": "sample_tool", "description": "A sample tool", "run_params_schema": {}, "init_params_schema": {}, "env_vars": []}],
     )
     mock_print_org.assert_called_once()
 
@@ -242,7 +248,12 @@ def test_publish_when_not_in_sync_and_force(
     "crewai.cli.tools.main.extract_available_exports",
     return_value=[{"name": "SampleTool"}],
 )
+@patch(
+    "crewai.cli.tools.main.extract_tools_metadata",
+    return_value=[{"name": "SampleTool", "humanized_name": "sample_tool", "description": "A sample tool", "run_params_schema": {}, "init_params_schema": {}, "env_vars": []}],
+)
 def test_publish_success(
+    mock_tools_metadata,
     mock_available_exports,
     mock_is_synced,
     mock_publish,
@@ -277,6 +288,7 @@ def test_publish_success(
         description="A sample tool",
         encoded_file=unittest.mock.ANY,
         available_exports=[{"name": "SampleTool"}],
+        tools_metadata=[{"name": "SampleTool", "humanized_name": "sample_tool", "description": "A sample tool", "run_params_schema": {}, "init_params_schema": {}, "env_vars": []}],
     )
 
 
@@ -295,7 +307,12 @@ def test_publish_success(
     "crewai.cli.tools.main.extract_available_exports",
     return_value=[{"name": "SampleTool"}],
 )
+@patch(
+    "crewai.cli.tools.main.extract_tools_metadata",
+    return_value=[{"name": "SampleTool", "humanized_name": "sample_tool", "description": "A sample tool", "run_params_schema": {}, "init_params_schema": {}, "env_vars": []}],
+)
 def test_publish_failure(
+    mock_tools_metadata,
     mock_available_exports,
     mock_publish,
     mock_open,
@@ -336,7 +353,12 @@ def test_publish_failure(
     "crewai.cli.tools.main.extract_available_exports",
     return_value=[{"name": "SampleTool"}],
 )
+@patch(
+    "crewai.cli.tools.main.extract_tools_metadata",
+    return_value=[{"name": "SampleTool", "humanized_name": "sample_tool", "description": "A sample tool", "run_params_schema": {}, "init_params_schema": {}, "env_vars": []}],
+)
 def test_publish_api_error(
+    mock_tools_metadata,
     mock_available_exports,
     mock_publish,
     mock_open,
@@ -362,6 +384,63 @@ def test_publish_api_error(
     mock_publish.assert_called_once()
 
 
+@patch("crewai.cli.tools.main.get_project_name", return_value="sample-tool")
+@patch("crewai.cli.tools.main.get_project_version", return_value="1.0.0")
+@patch("crewai.cli.tools.main.get_project_description", return_value="A sample tool")
+@patch("crewai.cli.tools.main.subprocess.run")
+@patch("crewai.cli.tools.main.os.listdir", return_value=["sample-tool-1.0.0.tar.gz"])
+@patch(
+    "crewai.cli.tools.main.open",
+    new_callable=unittest.mock.mock_open,
+    read_data=b"sample tarball content",
+)
+@patch("crewai.cli.plus_api.PlusAPI.publish_tool")
+@patch("crewai.cli.tools.main.git.Repository.is_synced", return_value=True)
+@patch(
+    "crewai.cli.tools.main.extract_available_exports",
+    return_value=[{"name": "SampleTool"}],
+)
+@patch(
+    "crewai.cli.tools.main.extract_tools_metadata",
+    side_effect=Exception("Failed to extract metadata"),
+)
+def test_publish_metadata_extraction_failure_continues_with_warning(
+    mock_tools_metadata,
+    mock_available_exports,
+    mock_is_synced,
+    mock_publish,
+    mock_open,
+    mock_listdir,
+    mock_subprocess_run,
+    mock_get_project_description,
+    mock_get_project_version,
+    mock_get_project_name,
+    capsys,
+    tool_command,
+):
+    """Test that metadata extraction failure shows warning but continues publishing."""
+    mock_publish_response = MagicMock()
+    mock_publish_response.status_code = 200
+    mock_publish_response.json.return_value = {"handle": "sample-tool"}
+    mock_publish.return_value = mock_publish_response
+
+    tool_command.publish(is_public=True)
+
+    output = capsys.readouterr().out
+    assert "Warning: Could not extract tool metadata" in output
+    assert "Publishing will continue without detailed metadata" in output
+    assert "No tool metadata extracted" in output
+    mock_publish.assert_called_once_with(
+        handle="sample-tool",
+        is_public=True,
+        version="1.0.0",
+        description="A sample tool",
+        encoded_file=unittest.mock.ANY,
+        available_exports=[{"name": "SampleTool"}],
+        tools_metadata=[],
+    )
+
+
 @patch("crewai.cli.tools.main.Settings")
 def test_print_current_organization_with_org(mock_settings, capsys, tool_command):
     mock_settings_instance = MagicMock()

lib/crewai/tests/llms/openai/test_openai.py

@@ -1523,6 +1523,69 @@ def test_openai_stop_words_not_applied_to_structured_output():
     assert "Observation:" in result.observation
 
 
+def test_openai_gpt5_models_do_not_support_stop_words():
+    """
+    Test that GPT-5 family models do not support stop words via the API.
+    GPT-5 models reject the 'stop' parameter, so stop words must be
+    applied client-side only.
+    """
+    gpt5_models = [
+        "gpt-5",
+        "gpt-5-mini",
+        "gpt-5-nano",
+        "gpt-5-pro",
+        "gpt-5.1",
+        "gpt-5.1-chat",
+        "gpt-5.2",
+        "gpt-5.2-chat",
+    ]
+
+    for model_name in gpt5_models:
+        llm = OpenAICompletion(model=model_name)
+        assert llm.supports_stop_words() == False, (
+            f"Expected {model_name} to NOT support stop words"
+        )
+
+
+def test_openai_non_gpt5_models_support_stop_words():
+    """
+    Test that non-GPT-5 models still support stop words normally.
+    """
+    supported_models = [
+        "gpt-4o",
+        "gpt-4o-mini",
+        "gpt-4.1",
+        "gpt-4.1-mini",
+        "gpt-4-turbo",
+    ]
+
+    for model_name in supported_models:
+        llm = OpenAICompletion(model=model_name)
+        assert llm.supports_stop_words() == True, (
+            f"Expected {model_name} to support stop words"
+        )
+
+
+def test_openai_gpt5_still_applies_stop_words_client_side():
+    """
+    Test that GPT-5 models still truncate responses at stop words client-side
+    via _apply_stop_words(), even though they don't send 'stop' to the API.
+    """
+    llm = OpenAICompletion(
+        model="gpt-5.2",
+        stop=["Observation:", "Final Answer:"],
+    )
+
+    assert llm.supports_stop_words() == False
+
+    response = "I need to search.\n\nAction: search\nObservation: Found results"
+    result = llm._apply_stop_words(response)
+
+    assert "Observation:" not in result
+    assert "Found results" not in result
+    assert "I need to search" in result
+
+
 def test_openai_stop_words_still_applied_to_regular_responses():
     """
     Test that stop words ARE still applied for regular (non-structured) responses.

lib/crewai/tests/mcp/test_stdio_config.py

@@ -0,0 +1,30 @@
+"""Tests for MCPServerStdio allowed_commands config integration."""
+
+import pytest
+
+from crewai.mcp.config import MCPServerStdio
+from crewai.mcp.transports.stdio import DEFAULT_ALLOWED_COMMANDS
+
+
+class TestMCPServerStdioConfig:
+    """Tests for the allowed_commands field on MCPServerStdio."""
+
+    def test_default_allowed_commands(self):
+        """MCPServerStdio should default to DEFAULT_ALLOWED_COMMANDS."""
+        config = MCPServerStdio(command="python", args=["server.py"])
+        assert config.allowed_commands == DEFAULT_ALLOWED_COMMANDS
+
+    def test_custom_allowed_commands(self):
+        """Users can override allowed_commands in config."""
+        custom = frozenset({"my-runtime"})
+        config = MCPServerStdio(
+            command="my-runtime", args=[], allowed_commands=custom
+        )
+        assert config.allowed_commands == custom
+
+    def test_none_allowed_commands(self):
+        """Users can disable the allowlist via config."""
+        config = MCPServerStdio(
+            command="anything", args=[], allowed_commands=None
+        )
+        assert config.allowed_commands is None

lib/crewai/tests/mcp/test_stdio_transport.py

@@ -0,0 +1,93 @@
+"""Tests for StdioTransport command allowlist validation."""
+
+import pytest
+
+from crewai.mcp.transports.stdio import DEFAULT_ALLOWED_COMMANDS, StdioTransport
+
+
+class TestStdioTransportAllowlist:
+    """Tests for the command allowlist feature."""
+
+    def test_default_allowed_commands_contains_common_runtimes(self):
+        """DEFAULT_ALLOWED_COMMANDS should include all common MCP server runtimes."""
+        expected = {"python", "python3", "node", "npx", "uvx", "uv", "deno", "docker"}
+        assert expected == DEFAULT_ALLOWED_COMMANDS
+
+    def test_allowed_command_passes_validation(self):
+        """Commands in the default allowlist should be accepted."""
+        for cmd in DEFAULT_ALLOWED_COMMANDS:
+            transport = StdioTransport(command=cmd, args=["server.py"])
+            assert transport.command == cmd
+
+    def test_allowed_command_with_full_path(self):
+        """Full paths to allowed commands should pass (basename is checked)."""
+        transport = StdioTransport(command="/usr/bin/python3", args=["server.py"])
+        assert transport.command == "/usr/bin/python3"
+
+    def test_disallowed_command_raises_value_error(self):
+        """Commands not in the allowlist should raise ValueError."""
+        with pytest.raises(ValueError, match="not in the allowed commands list"):
+            StdioTransport(command="malicious-binary", args=["--evil"])
+
+    def test_disallowed_command_with_full_path_raises(self):
+        """Full paths to disallowed commands should also be rejected."""
+        with pytest.raises(ValueError, match="not in the allowed commands list"):
+            StdioTransport(command="/tmp/evil/script", args=[])
+
+    def test_allowed_commands_none_disables_validation(self):
+        """Setting allowed_commands=None should disable the check entirely."""
+        transport = StdioTransport(
+            command="any-custom-binary",
+            args=["--flag"],
+            allowed_commands=None,
+        )
+        assert transport.command == "any-custom-binary"
+
+    def test_custom_allowlist(self):
+        """Users should be able to pass a custom allowlist."""
+        custom = frozenset({"my-server", "python"})
+
+        # Allowed
+        transport = StdioTransport(
+            command="my-server", args=[], allowed_commands=custom
+        )
+        assert transport.command == "my-server"
+
+        # Not allowed
+        with pytest.raises(ValueError, match="not in the allowed commands list"):
+            StdioTransport(command="node", args=[], allowed_commands=custom)
+
+    def test_extended_allowlist(self):
+        """Users should be able to extend the default allowlist."""
+        extended = DEFAULT_ALLOWED_COMMANDS | frozenset({"my-custom-runtime"})
+
+        transport = StdioTransport(
+            command="my-custom-runtime", args=[], allowed_commands=extended
+        )
+        assert transport.command == "my-custom-runtime"
+
+        # Original defaults still work
+        transport2 = StdioTransport(
+            command="python", args=["server.py"], allowed_commands=extended
+        )
+        assert transport2.command == "python"
+
+    def test_error_message_includes_sorted_allowed_commands(self):
+        """The error message should list the allowed commands for discoverability."""
+        with pytest.raises(ValueError) as exc_info:
+            StdioTransport(command="bad-cmd", args=[])
+
+        error_msg = str(exc_info.value)
+        assert "bad-cmd" in error_msg
+        assert "allowed_commands=None" in error_msg
+
+    def test_args_and_env_still_work(self):
+        """Existing args and env functionality should be unaffected."""
+        transport = StdioTransport(
+            command="python",
+            args=["server.py", "--port", "8080"],
+            env={"API_KEY": "test123"},
+        )
+        assert transport.command == "python"
+        assert transport.args == ["server.py", "--port", "8080"]
+        assert transport.env == {"API_KEY": "test123"}

lib/crewai/tests/test_llm.py

@@ -682,6 +682,126 @@ def test_llm_call_when_stop_is_unsupported_when_additional_drop_params_is_provid
     assert "Paris" in result
 
 
+@pytest.mark.vcr()
+def test_litellm_gpt5_call_succeeds_without_stop_error():
+    """
+    Integration test: GPT-5 call succeeds when stop words are configured,
+    because stop is omitted from API params and applied client-side.
+    """
+    llm = LLM(model="gpt-5", stop=["Observation:"], is_litellm=True)
+    result = llm.call("What is the capital of France?")
+    assert isinstance(result, str)
+    assert len(result) > 0
+
+
+def test_litellm_gpt5_does_not_send_stop_in_params():
+    """
+    Test that the LiteLLM fallback path does not include 'stop' in API params
+    for GPT-5.x models, since they reject it at the API level.
+    """
+    llm = LLM(model="openai/gpt-5.2", stop=["Observation:"], is_litellm=True)
+
+    params = llm._prepare_completion_params(
+        messages=[{"role": "user", "content": "Hello"}]
+    )
+
+    assert params.get("stop") is None, (
+        "GPT-5.x models should not have 'stop' in API params"
+    )
+
+
+def test_litellm_non_gpt5_sends_stop_in_params():
+    """
+    Test that the LiteLLM fallback path still includes 'stop' in API params
+    for models that support it.
+    """
+    llm = LLM(model="gpt-4o", stop=["Observation:"], is_litellm=True)
+
+    params = llm._prepare_completion_params(
+        messages=[{"role": "user", "content": "Hello"}]
+    )
+
+    assert params.get("stop") == ["Observation:"], (
+        "Non-GPT-5 models should have 'stop' in API params"
+    )
+
+
+def test_litellm_retry_catches_litellm_unsupported_params_error(caplog):
+    """
+    Test that the retry logic catches LiteLLM's UnsupportedParamsError format
+    ("does not support parameters") in addition to the OpenAI API format.
+    """
+    llm = LLM(model="openai/gpt-5.2", stop=["Observation:"], is_litellm=True)
+
+    litellm_error = Exception(
+        "litellm.UnsupportedParamsError: openai does not support parameters: "
+        "['stop'], for model=openai/gpt-5.2."
+    )
+
+    call_count = 0
+
+    try:
+        import litellm
+    except ImportError:
+        pytest.skip("litellm is not installed; skipping LiteLLM retry test")
+
+    def mock_completion(*args, **kwargs):
+        nonlocal call_count
+        call_count += 1
+        if call_count == 1:
+            raise litellm_error
+        return MagicMock(
+            choices=[MagicMock(message=MagicMock(content="Paris", tool_calls=None))],
+            usage=MagicMock(
+                prompt_tokens=10,
+                completion_tokens=5,
+                total_tokens=15,
+            ),
+        )
+
+    with patch("litellm.completion", side_effect=mock_completion):
+        with caplog.at_level(logging.INFO):
+            result = llm.call("What is the capital of France?")
+
+    assert "Retrying LLM call without the unsupported 'stop'" in caplog.text
+    assert "stop" in llm.additional_params.get("additional_drop_params", [])
+
+
+def test_litellm_retry_catches_openai_api_stop_error(caplog):
+    """
+    Test that the retry logic still catches the OpenAI API error format
+    ("Unsupported parameter: 'stop'").
+    """
+    llm = LLM(model="openai/gpt-5.2", stop=["Observation:"], is_litellm=True)
+
+    api_error = Exception(
+        "Unsupported parameter: 'stop' is not supported with this model."
+    )
+
+    call_count = 0
+
+    def mock_completion(*args, **kwargs):
+        nonlocal call_count
+        call_count += 1
+        if call_count == 1:
+            raise api_error
+        return MagicMock(
+            choices=[MagicMock(message=MagicMock(content="Paris", tool_calls=None))],
+            usage=MagicMock(
+                prompt_tokens=10,
+                completion_tokens=5,
+                total_tokens=15,
+            ),
+        )
+
+    with patch("litellm.completion", side_effect=mock_completion):
+        with caplog.at_level(logging.INFO):
+            llm.call("What is the capital of France?")
+
+    assert "Retrying LLM call without the unsupported 'stop'" in caplog.text
+    assert "stop" in llm.additional_params.get("additional_drop_params", [])
+
+
 @pytest.fixture
 def ollama_llm():
     return LLM(model="ollama/llama3.2:3b", is_litellm=True)