fix: Resolve test failures in HTTP MCP support tests

1. Fragment filtering test: Added proper assertion for MCPToolWrapper call
   and verified the mock tool is returned in the result list.

2. Logger patching tests: Changed from patching instance method to patching
   class method to avoid Pydantic's __delattr__ restriction. This prevents
   AttributeError when the patch context manager tries to restore the
   original attribute.

Co-Authored-By: João <joao@crewai.com>

lib/crewai-tools/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "pytube>=15.0.0",
     "requests>=2.32.5",
     "docker>=7.1.0",
-    "crewai==1.4.0",
+    "crewai==1.4.1",
     "lancedb>=0.5.4",
     "tiktoken>=0.8.0",
     "beautifulsoup4>=4.13.4",

lib/crewai-tools/src/crewai_tools/__init__.py

@@ -287,4 +287,4 @@ __all__ = [
     "ZapierActionTools",
 ]
 
-__version__ = "1.4.0"
+__version__ = "1.4.1"

lib/crewai/pyproject.toml

@@ -48,7 +48,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.4.0",
+    "crewai-tools==1.4.1",
 ]
 embeddings = [
     "tiktoken~=0.8.0"

lib/crewai/src/crewai/__init__.py

@@ -40,7 +40,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
 
 _suppress_pydantic_deprecation_warnings()
 
-__version__ = "1.4.0"
+__version__ = "1.4.1"
 _telemetry_submitted = False
 
 

lib/crewai/src/crewai/agent/core.py

@@ -713,7 +713,7 @@ class Agent(BaseAgent):
         """Get tools from legacy string-based MCP references.
 
         This method maintains backwards compatibility with string-based
-        MCP references (https://... and crewai-amp:...).
+        MCP references (http://..., https://..., and crewai-amp:...).
 
         Args:
             mcp_ref: String reference to MCP server.
@@ -723,12 +723,12 @@ class Agent(BaseAgent):
         """
         if mcp_ref.startswith("crewai-amp:"):
             return self._get_amp_mcp_tools(mcp_ref)
-        if mcp_ref.startswith("https://"):
+        if mcp_ref.startswith(("http://", "https://")):
             return self._get_external_mcp_tools(mcp_ref)
         return []
 
     def _get_external_mcp_tools(self, mcp_ref: str) -> list[BaseTool]:
-        """Get tools from external HTTPS MCP server with graceful error handling."""
+        """Get tools from external HTTP/HTTPS MCP server with graceful error handling."""
         from crewai.tools.mcp_tool_wrapper import MCPToolWrapper
 
         # Parse server URL and optional tool name
@@ -737,6 +737,15 @@ class Agent(BaseAgent):
         else:
             server_url, specific_tool = mcp_ref, None
 
+        parsed_url = urlparse(server_url)
+        if parsed_url.scheme == "http":
+            self._logger.log(
+                "warning",
+                f"Using http:// for MCP server '{server_url}'. "
+                "This is intended for local development only. "
+                "Use https:// in production to ensure secure communication.",
+            )
+
         server_params = {"url": server_url}
         server_name = self._extract_server_name(server_url)
 

lib/crewai/src/crewai/agents/agent_builder/base_agent.py

@@ -197,7 +197,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
     )
     mcps: list[str | MCPServerConfig] | None = Field(
         default=None,
-        description="List of MCP server references. Supports 'https://server.com/path' for external servers and 'crewai-amp:mcp-name' for AMP marketplace. Use '#tool_name' suffix for specific tools.",
+        description="List of MCP server references. Supports 'http://localhost:port/path' or 'https://server.com/path' for external servers and 'crewai-amp:mcp-name' for AMP marketplace. Use '#tool_name' suffix for specific tools. Note: http:// is intended for local development only; use https:// in production.",
     )
 
     @model_validator(mode="before")
@@ -268,12 +268,12 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         validated_mcps = []
         for mcp in mcps:
             if isinstance(mcp, str):
-                if mcp.startswith(("https://", "crewai-amp:")):
+                if mcp.startswith(("http://", "https://", "crewai-amp:")):
                     validated_mcps.append(mcp)
                 else:
                     raise ValueError(
                         f"Invalid MCP reference: {mcp}. "
-                        "String references must start with 'https://' or 'crewai-amp:'"
+                        "String references must start with 'http://', 'https://', or 'crewai-amp:'"
                     )
 
             elif isinstance(mcp, (MCPServerConfig)):

lib/crewai/src/crewai/agents/crew_agent_executor.py

@@ -214,6 +214,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         llm=self.llm,
                         callbacks=self.callbacks,
                     )
+                    break
 
                 enforce_rpm_limit(self.request_within_rpm_limit)
 
@@ -226,7 +227,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                     from_agent=self.agent,
                     response_model=self.response_model,
                 )
-                formatted_answer = process_llm_response(answer, self.use_stop_words)
+                formatted_answer = process_llm_response(answer, self.use_stop_words)  # type: ignore[assignment]
 
                 if isinstance(formatted_answer, AgentAction):
                     # Extract agent fingerprint if available
@@ -258,11 +259,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         formatted_answer, tool_result
                     )
 
-                self._invoke_step_callback(formatted_answer)
-                self._append_message(formatted_answer.text)
+                self._invoke_step_callback(formatted_answer)  # type: ignore[arg-type]
+                self._append_message(formatted_answer.text)  # type: ignore[union-attr,attr-defined]
 
-            except OutputParserError as e:  # noqa: PERF203
-                formatted_answer = handle_output_parser_exception(
+            except OutputParserError as e:
+                formatted_answer = handle_output_parser_exception(  # type: ignore[assignment]
                     e=e,
                     messages=self.messages,
                     iterations=self.iterations,

lib/crewai/src/crewai/cli/templates/crew/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.4.0"
+    "crewai[tools]==1.4.1"
 ]
 
 [project.scripts]

lib/crewai/src/crewai/cli/templates/flow/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.4.0"
+    "crewai[tools]==1.4.1"
 ]
 
 [project.scripts]

lib/crewai/src/crewai/llm.py

@@ -38,6 +38,13 @@ from crewai.events.types.tool_usage_events import (
     ToolUsageStartedEvent,
 )
 from crewai.llms.base_llm import BaseLLM
+from crewai.llms.constants import (
+    ANTHROPIC_MODELS,
+    AZURE_MODELS,
+    BEDROCK_MODELS,
+    GEMINI_MODELS,
+    OPENAI_MODELS,
+)
 from crewai.utilities import InternalInstructor
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededError,
@@ -323,18 +330,64 @@ class LLM(BaseLLM):
     completion_cost: float | None = None
 
     def __new__(cls, model: str, is_litellm: bool = False, **kwargs: Any) -> LLM:
-        """Factory method that routes to native SDK or falls back to LiteLLM."""
+        """Factory method that routes to native SDK or falls back to LiteLLM.
+
+        Routing priority:
+            1. If 'provider' kwarg is present, use that provider with constants
+            2. If only 'model' kwarg, use constants to infer provider
+            3. If "/" in model name:
+               - Check if prefix is a native provider (openai/anthropic/azure/bedrock/gemini)
+               - If yes, validate model against constants
+               - If valid, route to native SDK; otherwise route to LiteLLM
+        """
         if not model or not isinstance(model, str):
             raise ValueError("Model must be a non-empty string")
 
-        provider = model.partition("/")[0] if "/" in model else "openai"
+        explicit_provider = kwargs.get("provider")
 
-        native_class = cls._get_native_provider(provider)
+        if explicit_provider:
+            provider = explicit_provider
+            use_native = True
+            model_string = model
+        elif "/" in model:
+            prefix, _, model_part = model.partition("/")
+
+            provider_mapping = {
+                "openai": "openai",
+                "anthropic": "anthropic",
+                "claude": "anthropic",
+                "azure": "azure",
+                "azure_openai": "azure",
+                "google": "gemini",
+                "gemini": "gemini",
+                "bedrock": "bedrock",
+                "aws": "bedrock",
+            }
+
+            canonical_provider = provider_mapping.get(prefix.lower())
+
+            if canonical_provider and cls._validate_model_in_constants(
+                model_part, canonical_provider
+            ):
+                provider = canonical_provider
+                use_native = True
+                model_string = model_part
+            else:
+                provider = prefix
+                use_native = False
+                model_string = model_part
+        else:
+            provider = cls._infer_provider_from_model(model)
+            use_native = True
+            model_string = model
+
+        native_class = cls._get_native_provider(provider) if use_native else None
         if native_class and not is_litellm and provider in SUPPORTED_NATIVE_PROVIDERS:
             try:
-                model_string = model.partition("/")[2] if "/" in model else model
+                # Remove 'provider' from kwargs if it exists to avoid duplicate keyword argument
+                kwargs_copy = {k: v for k, v in kwargs.items() if k != 'provider'}
                 return cast(
-                    Self, native_class(model=model_string, provider=provider, **kwargs)
+                    Self, native_class(model=model_string, provider=provider, **kwargs_copy)
                 )
             except NotImplementedError:
                 raise
@@ -351,6 +404,63 @@ class LLM(BaseLLM):
         instance.is_litellm = True
         return instance
 
+    @classmethod
+    def _validate_model_in_constants(cls, model: str, provider: str) -> bool:
+        """Validate if a model name exists in the provider's constants.
+
+        Args:
+            model: The model name to validate
+            provider: The provider to check against (canonical name)
+
+        Returns:
+            True if the model exists in the provider's constants, False otherwise
+        """
+        if provider == "openai":
+            return model in OPENAI_MODELS
+
+        if provider == "anthropic" or provider == "claude":
+            return model in ANTHROPIC_MODELS
+
+        if provider == "gemini":
+            return model in GEMINI_MODELS
+
+        if provider == "bedrock":
+            return model in BEDROCK_MODELS
+
+        if provider == "azure":
+            # azure does not provide a list of available models, determine a better way to handle this
+            return True
+
+        return False
+
+    @classmethod
+    def _infer_provider_from_model(cls, model: str) -> str:
+        """Infer the provider from the model name.
+
+        Args:
+            model: The model name without provider prefix
+
+        Returns:
+            The inferred provider name, defaults to "openai"
+        """
+
+        if model in OPENAI_MODELS:
+            return "openai"
+
+        if model in ANTHROPIC_MODELS:
+            return "anthropic"
+
+        if model in GEMINI_MODELS:
+            return "gemini"
+
+        if model in BEDROCK_MODELS:
+            return "bedrock"
+
+        if model in AZURE_MODELS:
+            return "azure"
+
+        return "openai"
+
     @classmethod
     def _get_native_provider(cls, provider: str) -> type | None:
         """Get native provider class if available."""

lib/crewai/src/crewai/llms/constants.py

@@ -0,0 +1,558 @@
+from typing import Literal, TypeAlias
+
+
+OpenAIModels: TypeAlias = Literal[
+    "gpt-3.5-turbo",
+    "gpt-3.5-turbo-0125",
+    "gpt-3.5-turbo-0301",
+    "gpt-3.5-turbo-0613",
+    "gpt-3.5-turbo-1106",
+    "gpt-3.5-turbo-16k",
+    "gpt-3.5-turbo-16k-0613",
+    "gpt-3.5-turbo-instruct",
+    "gpt-3.5-turbo-instruct-0914",
+    "gpt-4",
+    "gpt-4-0125-preview",
+    "gpt-4-0314",
+    "gpt-4-0613",
+    "gpt-4-1106-preview",
+    "gpt-4-32k",
+    "gpt-4-32k-0314",
+    "gpt-4-32k-0613",
+    "gpt-4-turbo",
+    "gpt-4-turbo-2024-04-09",
+    "gpt-4-turbo-preview",
+    "gpt-4-vision-preview",
+    "gpt-4.1",
+    "gpt-4.1-2025-04-14",
+    "gpt-4.1-mini",
+    "gpt-4.1-mini-2025-04-14",
+    "gpt-4.1-nano",
+    "gpt-4.1-nano-2025-04-14",
+    "gpt-4o",
+    "gpt-4o-2024-05-13",
+    "gpt-4o-2024-08-06",
+    "gpt-4o-2024-11-20",
+    "gpt-4o-audio-preview",
+    "gpt-4o-audio-preview-2024-10-01",
+    "gpt-4o-audio-preview-2024-12-17",
+    "gpt-4o-audio-preview-2025-06-03",
+    "gpt-4o-mini",
+    "gpt-4o-mini-2024-07-18",
+    "gpt-4o-mini-audio-preview",
+    "gpt-4o-mini-audio-preview-2024-12-17",
+    "gpt-4o-mini-realtime-preview",
+    "gpt-4o-mini-realtime-preview-2024-12-17",
+    "gpt-4o-mini-search-preview",
+    "gpt-4o-mini-search-preview-2025-03-11",
+    "gpt-4o-mini-transcribe",
+    "gpt-4o-mini-tts",
+    "gpt-4o-realtime-preview",
+    "gpt-4o-realtime-preview-2024-10-01",
+    "gpt-4o-realtime-preview-2024-12-17",
+    "gpt-4o-realtime-preview-2025-06-03",
+    "gpt-4o-search-preview",
+    "gpt-4o-search-preview-2025-03-11",
+    "gpt-4o-transcribe",
+    "gpt-4o-transcribe-diarize",
+    "gpt-5",
+    "gpt-5-2025-08-07",
+    "gpt-5-chat",
+    "gpt-5-chat-latest",
+    "gpt-5-codex",
+    "gpt-5-mini",
+    "gpt-5-mini-2025-08-07",
+    "gpt-5-nano",
+    "gpt-5-nano-2025-08-07",
+    "gpt-5-pro",
+    "gpt-5-pro-2025-10-06",
+    "gpt-5-search-api",
+    "gpt-5-search-api-2025-10-14",
+    "gpt-audio",
+    "gpt-audio-2025-08-28",
+    "gpt-audio-mini",
+    "gpt-audio-mini-2025-10-06",
+    "gpt-image-1",
+    "gpt-image-1-mini",
+    "gpt-realtime",
+    "gpt-realtime-2025-08-28",
+    "gpt-realtime-mini",
+    "gpt-realtime-mini-2025-10-06",
+    "o1",
+    "o1-preview",
+    "o1-2024-12-17",
+    "o1-mini",
+    "o1-mini-2024-09-12",
+    "o1-pro",
+    "o1-pro-2025-03-19",
+    "o3-mini",
+    "o3",
+    "o4-mini",
+    "whisper-1",
+]
+OPENAI_MODELS: list[OpenAIModels] = [
+    "gpt-3.5-turbo",
+    "gpt-3.5-turbo-0125",
+    "gpt-3.5-turbo-0301",
+    "gpt-3.5-turbo-0613",
+    "gpt-3.5-turbo-1106",
+    "gpt-3.5-turbo-16k",
+    "gpt-3.5-turbo-16k-0613",
+    "gpt-3.5-turbo-instruct",
+    "gpt-3.5-turbo-instruct-0914",
+    "gpt-4",
+    "gpt-4-0125-preview",
+    "gpt-4-0314",
+    "gpt-4-0613",
+    "gpt-4-1106-preview",
+    "gpt-4-32k",
+    "gpt-4-32k-0314",
+    "gpt-4-32k-0613",
+    "gpt-4-turbo",
+    "gpt-4-turbo-2024-04-09",
+    "gpt-4-turbo-preview",
+    "gpt-4-vision-preview",
+    "gpt-4.1",
+    "gpt-4.1-2025-04-14",
+    "gpt-4.1-mini",
+    "gpt-4.1-mini-2025-04-14",
+    "gpt-4.1-nano",
+    "gpt-4.1-nano-2025-04-14",
+    "gpt-4o",
+    "gpt-4o-2024-05-13",
+    "gpt-4o-2024-08-06",
+    "gpt-4o-2024-11-20",
+    "gpt-4o-audio-preview",
+    "gpt-4o-audio-preview-2024-10-01",
+    "gpt-4o-audio-preview-2024-12-17",
+    "gpt-4o-audio-preview-2025-06-03",
+    "gpt-4o-mini",
+    "gpt-4o-mini-2024-07-18",
+    "gpt-4o-mini-audio-preview",
+    "gpt-4o-mini-audio-preview-2024-12-17",
+    "gpt-4o-mini-realtime-preview",
+    "gpt-4o-mini-realtime-preview-2024-12-17",
+    "gpt-4o-mini-search-preview",
+    "gpt-4o-mini-search-preview-2025-03-11",
+    "gpt-4o-mini-transcribe",
+    "gpt-4o-mini-tts",
+    "gpt-4o-realtime-preview",
+    "gpt-4o-realtime-preview-2024-10-01",
+    "gpt-4o-realtime-preview-2024-12-17",
+    "gpt-4o-realtime-preview-2025-06-03",
+    "gpt-4o-search-preview",
+    "gpt-4o-search-preview-2025-03-11",
+    "gpt-4o-transcribe",
+    "gpt-4o-transcribe-diarize",
+    "gpt-5",
+    "gpt-5-2025-08-07",
+    "gpt-5-chat",
+    "gpt-5-chat-latest",
+    "gpt-5-codex",
+    "gpt-5-mini",
+    "gpt-5-mini-2025-08-07",
+    "gpt-5-nano",
+    "gpt-5-nano-2025-08-07",
+    "gpt-5-pro",
+    "gpt-5-pro-2025-10-06",
+    "gpt-5-search-api",
+    "gpt-5-search-api-2025-10-14",
+    "gpt-audio",
+    "gpt-audio-2025-08-28",
+    "gpt-audio-mini",
+    "gpt-audio-mini-2025-10-06",
+    "gpt-image-1",
+    "gpt-image-1-mini",
+    "gpt-realtime",
+    "gpt-realtime-2025-08-28",
+    "gpt-realtime-mini",
+    "gpt-realtime-mini-2025-10-06",
+    "o1",
+    "o1-preview",
+    "o1-2024-12-17",
+    "o1-mini",
+    "o1-mini-2024-09-12",
+    "o1-pro",
+    "o1-pro-2025-03-19",
+    "o3-mini",
+    "o3",
+    "o4-mini",
+    "whisper-1",
+]
+
+
+AnthropicModels: TypeAlias = Literal[
+    "claude-3-7-sonnet-latest",
+    "claude-3-7-sonnet-20250219",
+    "claude-3-5-haiku-latest",
+    "claude-3-5-haiku-20241022",
+    "claude-haiku-4-5",
+    "claude-haiku-4-5-20251001",
+    "claude-sonnet-4-20250514",
+    "claude-sonnet-4-0",
+    "claude-4-sonnet-20250514",
+    "claude-sonnet-4-5",
+    "claude-sonnet-4-5-20250929",
+    "claude-3-5-sonnet-latest",
+    "claude-3-5-sonnet-20241022",
+    "claude-3-5-sonnet-20240620",
+    "claude-opus-4-0",
+    "claude-opus-4-20250514",
+    "claude-4-opus-20250514",
+    "claude-opus-4-1",
+    "claude-opus-4-1-20250805",
+    "claude-3-opus-latest",
+    "claude-3-opus-20240229",
+    "claude-3-sonnet-20240229",
+    "claude-3-haiku-latest",
+    "claude-3-haiku-20240307",
+]
+ANTHROPIC_MODELS: list[AnthropicModels] = [
+    "claude-3-7-sonnet-latest",
+    "claude-3-7-sonnet-20250219",
+    "claude-3-5-haiku-latest",
+    "claude-3-5-haiku-20241022",
+    "claude-haiku-4-5",
+    "claude-haiku-4-5-20251001",
+    "claude-sonnet-4-20250514",
+    "claude-sonnet-4-0",
+    "claude-4-sonnet-20250514",
+    "claude-sonnet-4-5",
+    "claude-sonnet-4-5-20250929",
+    "claude-3-5-sonnet-latest",
+    "claude-3-5-sonnet-20241022",
+    "claude-3-5-sonnet-20240620",
+    "claude-opus-4-0",
+    "claude-opus-4-20250514",
+    "claude-4-opus-20250514",
+    "claude-opus-4-1",
+    "claude-opus-4-1-20250805",
+    "claude-3-opus-latest",
+    "claude-3-opus-20240229",
+    "claude-3-sonnet-20240229",
+    "claude-3-haiku-latest",
+    "claude-3-haiku-20240307",
+]
+
+GeminiModels: TypeAlias = Literal[
+    "gemini-2.5-pro",
+    "gemini-2.5-pro-preview-03-25",
+    "gemini-2.5-pro-preview-05-06",
+    "gemini-2.5-pro-preview-06-05",
+    "gemini-2.5-flash",
+    "gemini-2.5-flash-preview-05-20",
+    "gemini-2.5-flash-preview-04-17",
+    "gemini-2.5-flash-image",
+    "gemini-2.5-flash-image-preview",
+    "gemini-2.5-flash-lite",
+    "gemini-2.5-flash-lite-preview-06-17",
+    "gemini-2.5-flash-preview-09-2025",
+    "gemini-2.5-flash-lite-preview-09-2025",
+    "gemini-2.5-flash-preview-tts",
+    "gemini-2.5-pro-preview-tts",
+    "gemini-2.5-computer-use-preview-10-2025",
+    "gemini-2.0-flash",
+    "gemini-2.0-flash-001",
+    "gemini-2.0-flash-exp",
+    "gemini-2.0-flash-exp-image-generation",
+    "gemini-2.0-flash-lite",
+    "gemini-2.0-flash-lite-001",
+    "gemini-2.0-flash-lite-preview",
+    "gemini-2.0-flash-lite-preview-02-05",
+    "gemini-2.0-flash-preview-image-generation",
+    "gemini-2.0-flash-thinking-exp",
+    "gemini-2.0-flash-thinking-exp-01-21",
+    "gemini-2.0-flash-thinking-exp-1219",
+    "gemini-2.0-pro-exp",
+    "gemini-2.0-pro-exp-02-05",
+    "gemini-exp-1206",
+    "gemini-1.5-pro",
+    "gemini-1.5-flash",
+    "gemini-1.5-flash-8b",
+    "gemini-flash-latest",
+    "gemini-flash-lite-latest",
+    "gemini-pro-latest",
+    "gemini-2.0-flash-live-001",
+    "gemini-live-2.5-flash-preview",
+    "gemini-2.5-flash-live-preview",
+    "gemini-robotics-er-1.5-preview",
+    "gemini-gemma-2-27b-it",
+    "gemini-gemma-2-9b-it",
+    "gemma-3-1b-it",
+    "gemma-3-4b-it",
+    "gemma-3-12b-it",
+    "gemma-3-27b-it",
+    "gemma-3n-e2b-it",
+    "gemma-3n-e4b-it",
+    "learnlm-2.0-flash-experimental",
+]
+GEMINI_MODELS: list[GeminiModels] = [
+    "gemini-2.5-pro",
+    "gemini-2.5-pro-preview-03-25",
+    "gemini-2.5-pro-preview-05-06",
+    "gemini-2.5-pro-preview-06-05",
+    "gemini-2.5-flash",
+    "gemini-2.5-flash-preview-05-20",
+    "gemini-2.5-flash-preview-04-17",
+    "gemini-2.5-flash-image",
+    "gemini-2.5-flash-image-preview",
+    "gemini-2.5-flash-lite",
+    "gemini-2.5-flash-lite-preview-06-17",
+    "gemini-2.5-flash-preview-09-2025",
+    "gemini-2.5-flash-lite-preview-09-2025",
+    "gemini-2.5-flash-preview-tts",
+    "gemini-2.5-pro-preview-tts",
+    "gemini-2.5-computer-use-preview-10-2025",
+    "gemini-2.0-flash",
+    "gemini-2.0-flash-001",
+    "gemini-2.0-flash-exp",
+    "gemini-2.0-flash-exp-image-generation",
+    "gemini-2.0-flash-lite",
+    "gemini-2.0-flash-lite-001",
+    "gemini-2.0-flash-lite-preview",
+    "gemini-2.0-flash-lite-preview-02-05",
+    "gemini-2.0-flash-preview-image-generation",
+    "gemini-2.0-flash-thinking-exp",
+    "gemini-2.0-flash-thinking-exp-01-21",
+    "gemini-2.0-flash-thinking-exp-1219",
+    "gemini-2.0-pro-exp",
+    "gemini-2.0-pro-exp-02-05",
+    "gemini-exp-1206",
+    "gemini-1.5-pro",
+    "gemini-1.5-flash",
+    "gemini-1.5-flash-8b",
+    "gemini-flash-latest",
+    "gemini-flash-lite-latest",
+    "gemini-pro-latest",
+    "gemini-2.0-flash-live-001",
+    "gemini-live-2.5-flash-preview",
+    "gemini-2.5-flash-live-preview",
+    "gemini-robotics-er-1.5-preview",
+    "gemini-gemma-2-27b-it",
+    "gemini-gemma-2-9b-it",
+    "gemma-3-1b-it",
+    "gemma-3-4b-it",
+    "gemma-3-12b-it",
+    "gemma-3-27b-it",
+    "gemma-3n-e2b-it",
+    "gemma-3n-e4b-it",
+    "learnlm-2.0-flash-experimental",
+]
+
+
+AzureModels: TypeAlias = Literal[
+    "gpt-3.5-turbo",
+    "gpt-3.5-turbo-0301",
+    "gpt-3.5-turbo-0613",
+    "gpt-3.5-turbo-16k",
+    "gpt-3.5-turbo-16k-0613",
+    "gpt-35-turbo",
+    "gpt-35-turbo-0125",
+    "gpt-35-turbo-1106",
+    "gpt-35-turbo-16k-0613",
+    "gpt-35-turbo-instruct-0914",
+    "gpt-4",
+    "gpt-4-0314",
+    "gpt-4-0613",
+    "gpt-4-1106-preview",
+    "gpt-4-0125-preview",
+    "gpt-4-32k",
+    "gpt-4-32k-0314",
+    "gpt-4-32k-0613",
+    "gpt-4-turbo",
+    "gpt-4-turbo-2024-04-09",
+    "gpt-4-vision",
+    "gpt-4o",
+    "gpt-4o-2024-05-13",
+    "gpt-4o-2024-08-06",
+    "gpt-4o-2024-11-20",
+    "gpt-4o-mini",
+    "gpt-5",
+    "o1",
+    "o1-mini",
+    "o1-preview",
+    "o3-mini",
+    "o3",
+    "o4-mini",
+]
+AZURE_MODELS: list[AzureModels] = [
+    "gpt-3.5-turbo",
+    "gpt-3.5-turbo-0301",
+    "gpt-3.5-turbo-0613",
+    "gpt-3.5-turbo-16k",
+    "gpt-3.5-turbo-16k-0613",
+    "gpt-35-turbo",
+    "gpt-35-turbo-0125",
+    "gpt-35-turbo-1106",
+    "gpt-35-turbo-16k-0613",
+    "gpt-35-turbo-instruct-0914",
+    "gpt-4",
+    "gpt-4-0314",
+    "gpt-4-0613",
+    "gpt-4-1106-preview",
+    "gpt-4-0125-preview",
+    "gpt-4-32k",
+    "gpt-4-32k-0314",
+    "gpt-4-32k-0613",
+    "gpt-4-turbo",
+    "gpt-4-turbo-2024-04-09",
+    "gpt-4-vision",
+    "gpt-4o",
+    "gpt-4o-2024-05-13",
+    "gpt-4o-2024-08-06",
+    "gpt-4o-2024-11-20",
+    "gpt-4o-mini",
+    "gpt-5",
+    "o1",
+    "o1-mini",
+    "o1-preview",
+    "o3-mini",
+    "o3",
+    "o4-mini",
+]
+
+
+BedrockModels: TypeAlias = Literal[
+    "ai21.jamba-1-5-large-v1:0",
+    "ai21.jamba-1-5-mini-v1:0",
+    "amazon.nova-lite-v1:0",
+    "amazon.nova-lite-v1:0:24k",
+    "amazon.nova-lite-v1:0:300k",
+    "amazon.nova-micro-v1:0",
+    "amazon.nova-micro-v1:0:128k",
+    "amazon.nova-micro-v1:0:24k",
+    "amazon.nova-premier-v1:0",
+    "amazon.nova-premier-v1:0:1000k",
+    "amazon.nova-premier-v1:0:20k",
+    "amazon.nova-premier-v1:0:8k",
+    "amazon.nova-premier-v1:0:mm",
+    "amazon.nova-pro-v1:0",
+    "amazon.nova-pro-v1:0:24k",
+    "amazon.nova-pro-v1:0:300k",
+    "amazon.titan-text-express-v1",
+    "amazon.titan-text-express-v1:0:8k",
+    "amazon.titan-text-lite-v1",
+    "amazon.titan-text-lite-v1:0:4k",
+    "amazon.titan-tg1-large",
+    "anthropic.claude-3-5-haiku-20241022-v1:0",
+    "anthropic.claude-3-5-sonnet-20240620-v1:0",
+    "anthropic.claude-3-5-sonnet-20241022-v2:0",
+    "anthropic.claude-3-7-sonnet-20250219-v1:0",
+    "anthropic.claude-3-haiku-20240307-v1:0",
+    "anthropic.claude-3-haiku-20240307-v1:0:200k",
+    "anthropic.claude-3-haiku-20240307-v1:0:48k",
+    "anthropic.claude-3-opus-20240229-v1:0",
+    "anthropic.claude-3-opus-20240229-v1:0:12k",
+    "anthropic.claude-3-opus-20240229-v1:0:200k",
+    "anthropic.claude-3-opus-20240229-v1:0:28k",
+    "anthropic.claude-3-sonnet-20240229-v1:0",
+    "anthropic.claude-3-sonnet-20240229-v1:0:200k",
+    "anthropic.claude-3-sonnet-20240229-v1:0:28k",
+    "anthropic.claude-haiku-4-5-20251001-v1:0",
+    "anthropic.claude-instant-v1:2:100k",
+    "anthropic.claude-opus-4-1-20250805-v1:0",
+    "anthropic.claude-opus-4-20250514-v1:0",
+    "anthropic.claude-sonnet-4-20250514-v1:0",
+    "anthropic.claude-sonnet-4-5-20250929-v1:0",
+    "anthropic.claude-v2:0:100k",
+    "anthropic.claude-v2:0:18k",
+    "anthropic.claude-v2:1:18k",
+    "anthropic.claude-v2:1:200k",
+    "cohere.command-r-plus-v1:0",
+    "cohere.command-r-v1:0",
+    "cohere.rerank-v3-5:0",
+    "deepseek.r1-v1:0",
+    "meta.llama3-1-70b-instruct-v1:0",
+    "meta.llama3-1-8b-instruct-v1:0",
+    "meta.llama3-2-11b-instruct-v1:0",
+    "meta.llama3-2-1b-instruct-v1:0",
+    "meta.llama3-2-3b-instruct-v1:0",
+    "meta.llama3-2-90b-instruct-v1:0",
+    "meta.llama3-3-70b-instruct-v1:0",
+    "meta.llama3-70b-instruct-v1:0",
+    "meta.llama3-8b-instruct-v1:0",
+    "meta.llama4-maverick-17b-instruct-v1:0",
+    "meta.llama4-scout-17b-instruct-v1:0",
+    "mistral.mistral-7b-instruct-v0:2",
+    "mistral.mistral-large-2402-v1:0",
+    "mistral.mistral-small-2402-v1:0",
+    "mistral.mixtral-8x7b-instruct-v0:1",
+    "mistral.pixtral-large-2502-v1:0",
+    "openai.gpt-oss-120b-1:0",
+    "openai.gpt-oss-20b-1:0",
+    "qwen.qwen3-32b-v1:0",
+    "qwen.qwen3-coder-30b-a3b-v1:0",
+    "twelvelabs.pegasus-1-2-v1:0",
+]
+BEDROCK_MODELS: list[BedrockModels] = [
+    "ai21.jamba-1-5-large-v1:0",
+    "ai21.jamba-1-5-mini-v1:0",
+    "amazon.nova-lite-v1:0",
+    "amazon.nova-lite-v1:0:24k",
+    "amazon.nova-lite-v1:0:300k",
+    "amazon.nova-micro-v1:0",
+    "amazon.nova-micro-v1:0:128k",
+    "amazon.nova-micro-v1:0:24k",
+    "amazon.nova-premier-v1:0",
+    "amazon.nova-premier-v1:0:1000k",
+    "amazon.nova-premier-v1:0:20k",
+    "amazon.nova-premier-v1:0:8k",
+    "amazon.nova-premier-v1:0:mm",
+    "amazon.nova-pro-v1:0",
+    "amazon.nova-pro-v1:0:24k",
+    "amazon.nova-pro-v1:0:300k",
+    "amazon.titan-text-express-v1",
+    "amazon.titan-text-express-v1:0:8k",
+    "amazon.titan-text-lite-v1",
+    "amazon.titan-text-lite-v1:0:4k",
+    "amazon.titan-tg1-large",
+    "anthropic.claude-3-5-haiku-20241022-v1:0",
+    "anthropic.claude-3-5-sonnet-20240620-v1:0",
+    "anthropic.claude-3-5-sonnet-20241022-v2:0",
+    "anthropic.claude-3-7-sonnet-20250219-v1:0",
+    "anthropic.claude-3-haiku-20240307-v1:0",
+    "anthropic.claude-3-haiku-20240307-v1:0:200k",
+    "anthropic.claude-3-haiku-20240307-v1:0:48k",
+    "anthropic.claude-3-opus-20240229-v1:0",
+    "anthropic.claude-3-opus-20240229-v1:0:12k",
+    "anthropic.claude-3-opus-20240229-v1:0:200k",
+    "anthropic.claude-3-opus-20240229-v1:0:28k",
+    "anthropic.claude-3-sonnet-20240229-v1:0",
+    "anthropic.claude-3-sonnet-20240229-v1:0:200k",
+    "anthropic.claude-3-sonnet-20240229-v1:0:28k",
+    "anthropic.claude-haiku-4-5-20251001-v1:0",
+    "anthropic.claude-instant-v1:2:100k",
+    "anthropic.claude-opus-4-1-20250805-v1:0",
+    "anthropic.claude-opus-4-20250514-v1:0",
+    "anthropic.claude-sonnet-4-20250514-v1:0",
+    "anthropic.claude-sonnet-4-5-20250929-v1:0",
+    "anthropic.claude-v2:0:100k",
+    "anthropic.claude-v2:0:18k",
+    "anthropic.claude-v2:1:18k",
+    "anthropic.claude-v2:1:200k",
+    "cohere.command-r-plus-v1:0",
+    "cohere.command-r-v1:0",
+    "cohere.rerank-v3-5:0",
+    "deepseek.r1-v1:0",
+    "meta.llama3-1-70b-instruct-v1:0",
+    "meta.llama3-1-8b-instruct-v1:0",
+    "meta.llama3-2-11b-instruct-v1:0",
+    "meta.llama3-2-1b-instruct-v1:0",
+    "meta.llama3-2-3b-instruct-v1:0",
+    "meta.llama3-2-90b-instruct-v1:0",
+    "meta.llama3-3-70b-instruct-v1:0",
+    "meta.llama3-70b-instruct-v1:0",
+    "meta.llama3-8b-instruct-v1:0",
+    "meta.llama4-maverick-17b-instruct-v1:0",
+    "meta.llama4-scout-17b-instruct-v1:0",
+    "mistral.mistral-7b-instruct-v0:2",
+    "mistral.mistral-large-2402-v1:0",
+    "mistral.mistral-small-2402-v1:0",
+    "mistral.mixtral-8x7b-instruct-v0:1",
+    "mistral.pixtral-large-2502-v1:0",
+    "openai.gpt-oss-120b-1:0",
+    "openai.gpt-oss-20b-1:0",
+    "qwen.qwen3-32b-v1:0",
+    "qwen.qwen3-coder-30b-a3b-v1:0",
+    "twelvelabs.pegasus-1-2-v1:0",
+]

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

@@ -63,6 +63,11 @@ class MCPServerHTTP(BaseModel):
             headers={"Authorization": "Bearer ..."},
             cache_tools_list=True,
         )
+
+        mcp_server = MCPServerHTTP(
+            url="http://localhost:8000/mcp",
+            cache_tools_list=True,
+        )
         ```
     """
 

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

@@ -28,6 +28,11 @@ class HTTPTransport(BaseTransport):
             url="https://api.example.com/mcp",
             headers={"Authorization": "Bearer ..."}
         )
+
+        transport = HTTPTransport(
+            url="http://localhost:8000/mcp"
+        )
+
         async with transport:
             # Use transport...
         ```

lib/crewai/src/crewai/utilities/agent_utils.py

@@ -127,7 +127,7 @@ def handle_max_iterations_exceeded(
     messages: list[LLMMessage],
     llm: LLM | BaseLLM,
     callbacks: list[TokenCalcHandler],
-) -> AgentAction | AgentFinish:
+) -> AgentFinish:
     """Handles the case when the maximum number of iterations is exceeded. Performs one more LLM call to get the final answer.
 
     Args:
@@ -139,7 +139,7 @@ def handle_max_iterations_exceeded(
         callbacks: List of callbacks for the LLM call.
 
     Returns:
-        The final formatted answer after exceeding max iterations.
+        AgentFinish with the final answer after exceeding max iterations.
     """
     printer.print(
         content="Maximum iterations reached. Requesting final answer.",
@@ -157,7 +157,7 @@ def handle_max_iterations_exceeded(
 
     # Perform one more LLM call to get the final answer
     answer = llm.call(
-        messages,  # type: ignore[arg-type]
+        messages,
         callbacks=callbacks,
     )
 
@@ -168,8 +168,16 @@ def handle_max_iterations_exceeded(
         )
         raise ValueError("Invalid response from LLM call - None or empty.")
 
-    # Return the formatted answer, regardless of its type
-    return format_answer(answer=answer)
+    formatted = format_answer(answer=answer)
+
+    # If format_answer returned an AgentAction, convert it to AgentFinish
+    if isinstance(formatted, AgentFinish):
+        return formatted
+    return AgentFinish(
+        thought=formatted.thought,
+        output=formatted.text,
+        text=formatted.text,
+    )
 
 
 def format_message_for_llm(
@@ -249,10 +257,10 @@ def get_llm_response(
     """
     try:
         answer = llm.call(
-            messages,  # type: ignore[arg-type]
+            messages,
             callbacks=callbacks,
             from_task=from_task,
-            from_agent=from_agent,
+            from_agent=from_agent,  # type: ignore[arg-type]
             response_model=response_model,
         )
     except Exception as e:
@@ -294,8 +302,8 @@ def handle_agent_action_core(
     formatted_answer: AgentAction,
     tool_result: ToolResult,
     messages: list[LLMMessage] | None = None,
-    step_callback: Callable | None = None,
-    show_logs: Callable | None = None,
+    step_callback: Callable | None = None,  # type: ignore[type-arg]
+    show_logs: Callable | None = None,  # type: ignore[type-arg]
 ) -> AgentAction | AgentFinish:
     """Core logic for handling agent actions and tool results.
 
@@ -481,7 +489,7 @@ def summarize_messages(
             ),
         ]
         summary = llm.call(
-            messages,  # type: ignore[arg-type]
+            messages,
             callbacks=callbacks,
         )
         summarized_contents.append({"content": str(summary)})

lib/crewai/tests/agents/test_agent.py

@@ -508,7 +508,47 @@ def test_agent_custom_max_iterations():
     assert isinstance(result, str)
     assert len(result) > 0
     assert call_count > 0
-    assert call_count == 3
+    # With max_iter=1, expect 2 calls:
+    # - Call 1: iteration 0
+    # - Call 2: iteration 1 (max reached, handle_max_iterations_exceeded called, then loop breaks)
+    assert call_count == 2
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+@pytest.mark.timeout(30)
+def test_agent_max_iterations_stops_loop():
+    """Test that agent execution terminates when max_iter is reached."""
+
+    @tool
+    def get_data(step: str) -> str:
+        """Get data for a step. Always returns data requiring more steps."""
+        return f"Data for {step}: incomplete, need to query more steps."
+
+    agent = Agent(
+        role="data collector",
+        goal="collect data using the get_data tool",
+        backstory="You must use the get_data tool extensively",
+        max_iter=2,
+        allow_delegation=False,
+    )
+
+    task = Task(
+        description="Use get_data tool for step1, step2, step3, step4, step5, step6, step7, step8, step9, and step10. Do NOT stop until you've called it for ALL steps.",
+        expected_output="A summary of all data collected",
+    )
+
+    result = agent.execute_task(
+        task=task,
+        tools=[get_data],
+    )
+
+    assert result is not None
+    assert isinstance(result, str)
+
+    assert agent.agent_executor.iterations <= agent.max_iter + 2, (
+        f"Agent ran {agent.agent_executor.iterations} iterations "
+        f"but should stop around {agent.max_iter + 1}. "
+    )
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])

lib/crewai/tests/cassettes/test_agent_max_iterations_stops_loop.yaml

@@ -0,0 +1,495 @@
+interactions:
+- request:
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+    headers:
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+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate, zstd
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '434'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - CrewAI-CLI/1.4.0
+      X-Crewai-Version:
+      - 1.4.0
+    method: POST
+    uri: https://app.crewai.com/crewai_plus/api/v1/tracing/batches
+  response:
+    body:
+      string: '{"error":"bad_credentials","message":"Bad credentials"}'
+    headers:
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '55'
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Fri, 07 Nov 2025 18:27:07 GMT
+      cache-control:
+      - no-store
+      content-security-policy:
+      - 'default-src ''self'' *.app.crewai.com app.crewai.com; script-src ''self''
+        ''unsafe-inline'' *.app.crewai.com app.crewai.com https://cdn.jsdelivr.net/npm/apexcharts
+        https://www.gstatic.com https://run.pstmn.io https://apis.google.com https://apis.google.com/js/api.js
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lib/crewai/tests/llms/anthropic/test_anthropic.py

@@ -36,7 +36,7 @@ def test_anthropic_completion_is_used_when_claude_provider():
 
     from crewai.llms.providers.anthropic.completion import AnthropicCompletion
     assert isinstance(llm, AnthropicCompletion)
-    assert llm.provider == "claude"
+    assert llm.provider == "anthropic"
     assert llm.model == "claude-3-5-sonnet-20241022"
 
 

lib/crewai/tests/llms/azure/test_azure.py

@@ -39,7 +39,7 @@ def test_azure_completion_is_used_when_azure_openai_provider():
 
     from crewai.llms.providers.azure.completion import AzureCompletion
     assert isinstance(llm, AzureCompletion)
-    assert llm.provider == "azure_openai"
+    assert llm.provider == "azure"
     assert llm.model == "gpt-4"
 
 

lib/crewai/tests/llms/google/test_google.py

@@ -24,7 +24,7 @@ def test_gemini_completion_is_used_when_google_provider():
     llm = LLM(model="google/gemini-2.0-flash-001")
 
     assert llm.__class__.__name__ == "GeminiCompletion"
-    assert llm.provider == "google"
+    assert llm.provider == "gemini"
     assert llm.model == "gemini-2.0-flash-001"
 
 

lib/crewai/tests/llms/hooks/test_unsupported_providers.py

@@ -154,7 +154,7 @@ class TestGeminiProviderInterceptor:
         # Gemini provider should raise NotImplementedError
         with pytest.raises(NotImplementedError) as exc_info:
             LLM(
-                model="gemini/gemini-pro",
+                model="gemini/gemini-2.5-pro",
                 interceptor=interceptor,
                 api_key="test-gemini-key",
             )
@@ -169,7 +169,7 @@ class TestGeminiProviderInterceptor:
 
         with pytest.raises(NotImplementedError) as exc_info:
             LLM(
-                model="gemini/gemini-pro",
+                model="gemini/gemini-2.5-pro",
                 interceptor=interceptor,
                 api_key="test-gemini-key",
             )
@@ -181,7 +181,7 @@ class TestGeminiProviderInterceptor:
     def test_gemini_without_interceptor_works(self) -> None:
         """Test that Gemini LLM works without interceptor."""
         llm = LLM(
-            model="gemini/gemini-pro",
+            model="gemini/gemini-2.5-pro",
             api_key="test-gemini-key",
         )
 
@@ -231,7 +231,7 @@ class TestUnsupportedProviderMessages:
 
         with pytest.raises(NotImplementedError) as exc_info:
             LLM(
-                model="gemini/gemini-pro",
+                model="gemini/gemini-2.5-pro",
                 interceptor=interceptor,
                 api_key="test-gemini-key",
             )
@@ -282,7 +282,7 @@ class TestProviderSupportMatrix:
         # Gemini - NOT SUPPORTED
         with pytest.raises(NotImplementedError):
             LLM(
-                model="gemini/gemini-pro",
+                model="gemini/gemini-2.5-pro",
                 interceptor=interceptor,
                 api_key="test",
             )
@@ -315,5 +315,5 @@ class TestProviderSupportMatrix:
         assert not hasattr(bedrock_llm, 'interceptor') or bedrock_llm.interceptor is None
 
         # Gemini - doesn't have interceptor attribute
-        gemini_llm = LLM(model="gemini/gemini-pro", api_key="test")
-        assert not hasattr(gemini_llm, 'interceptor') or gemini_llm.interceptor is None
+        gemini_llm = LLM(model="gemini/gemini-2.5-pro", api_key="test")
+        assert not hasattr(gemini_llm, 'interceptor') or gemini_llm.interceptor is None

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

@@ -16,7 +16,7 @@ def test_openai_completion_is_used_when_openai_provider():
     """
     Test that OpenAICompletion from completion.py is used when LLM uses provider 'openai'
     """
-    llm = LLM(model="openai/gpt-4o")
+    llm = LLM(model="gpt-4o")
 
     assert llm.__class__.__name__ == "OpenAICompletion"
     assert llm.provider == "openai"
@@ -70,7 +70,7 @@ def test_openai_completion_module_is_imported():
         del sys.modules[module_name]
 
     # Create LLM instance - this should trigger the import
-    LLM(model="openai/gpt-4o")
+    LLM(model="gpt-4o")
 
     # Verify the module was imported
     assert module_name in sys.modules
@@ -97,7 +97,7 @@ def test_native_openai_raises_error_when_initialization_fails():
 
         # This should raise ImportError, not fall back to LiteLLM
         with pytest.raises(ImportError) as excinfo:
-            LLM(model="openai/gpt-4o")
+            LLM(model="gpt-4o")
 
         assert "Error importing native provider" in str(excinfo.value)
         assert "Native SDK failed" in str(excinfo.value)
@@ -108,7 +108,7 @@ def test_openai_completion_initialization_parameters():
     Test that OpenAICompletion is initialized with correct parameters
     """
     llm = LLM(
-        model="openai/gpt-4o",
+        model="gpt-4o",
         temperature=0.7,
         max_tokens=1000,
         api_key="test-key"
@@ -311,7 +311,7 @@ def test_openai_completion_call_returns_usage_metrics():
         role="Research Assistant",
         goal="Find information about the population of Tokyo",
         backstory="You are a helpful research assistant.",
-        llm=LLM(model="openai/gpt-4o"),
+        llm=LLM(model="gpt-4o"),
         verbose=True,
     )
 
@@ -331,6 +331,7 @@ def test_openai_completion_call_returns_usage_metrics():
     assert result.token_usage.cached_prompt_tokens == 0
 
 
+@pytest.mark.skip(reason="Allow for litellm")
 def test_openai_raises_error_when_model_not_supported():
     """Test that OpenAICompletion raises ValueError when model not supported"""
 
@@ -354,7 +355,7 @@ def test_openai_client_setup_with_extra_arguments():
     Test that OpenAICompletion is initialized with correct parameters
     """
     llm = LLM(
-        model="openai/gpt-4o",
+        model="gpt-4o",
         temperature=0.7,
         max_tokens=1000,
         top_p=0.5,
@@ -391,7 +392,7 @@ def test_extra_arguments_are_passed_to_openai_completion():
     """
     Test that extra arguments are passed to OpenAICompletion
     """
-    llm = LLM(model="openai/gpt-4o", temperature=0.7, max_tokens=1000, top_p=0.5, max_retries=3)
+    llm = LLM(model="gpt-4o", temperature=0.7, max_tokens=1000, top_p=0.5, max_retries=3)
 
     with patch.object(llm.client.chat.completions, 'create') as mock_create:
         mock_create.return_value = MagicMock(

lib/crewai/tests/mcp/test_http_mcp_support.py

@@ -0,0 +1,216 @@
+"""Tests for HTTP MCP server support (issue #3876)."""
+
+import pytest
+from unittest.mock import MagicMock, patch
+
+from crewai.agent.core import Agent
+from crewai.mcp.config import MCPServerHTTP
+
+
+class TestHTTPMCPValidation:
+    """Test validation of HTTP MCP URLs."""
+
+    def test_validator_accepts_http_urls(self):
+        """Test that validator accepts http:// URLs."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+            mcps=["http://localhost:7365/mcp"],
+        )
+        assert agent.mcps == ["http://localhost:7365/mcp"]
+
+    def test_validator_accepts_https_urls(self):
+        """Test that validator still accepts https:// URLs."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+            mcps=["https://api.example.com/mcp"],
+        )
+        assert agent.mcps == ["https://api.example.com/mcp"]
+
+    def test_validator_accepts_crewai_amp_urls(self):
+        """Test that validator still accepts crewai-amp: URLs."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+            mcps=["crewai-amp:mcp-name"],
+        )
+        assert agent.mcps == ["crewai-amp:mcp-name"]
+
+    def test_validator_accepts_http_with_fragment(self):
+        """Test that validator accepts http:// URLs with #tool fragment."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+            mcps=["http://localhost:7365/mcp#diff_general_info"],
+        )
+        assert agent.mcps == ["http://localhost:7365/mcp#diff_general_info"]
+
+    def test_validator_rejects_unsupported_schemes(self):
+        """Test that validator rejects unsupported URL schemes with updated error message."""
+        with pytest.raises(ValueError) as exc_info:
+            Agent(
+                role="Test Agent",
+                goal="Test goal",
+                backstory="Test backstory",
+                mcps=["ftp://example.com/mcp"],
+            )
+        
+        error_message = str(exc_info.value)
+        assert "Invalid MCP reference: ftp://example.com/mcp" in error_message
+        assert "http://" in error_message
+        assert "https://" in error_message
+        assert "crewai-amp:" in error_message
+
+
+class TestHTTPMCPRouting:
+    """Test routing of HTTP MCP URLs."""
+
+    def test_get_mcp_tools_from_string_routes_http_urls(self):
+        """Test that _get_mcp_tools_from_string routes http:// URLs correctly."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+        )
+        
+        sentinel_tools = [MagicMock()]
+        
+        with patch.object(agent, '_get_external_mcp_tools', return_value=sentinel_tools) as mock_external:
+            result = agent._get_mcp_tools_from_string("http://localhost:7365/mcp")
+            
+            assert result == sentinel_tools
+            mock_external.assert_called_once_with("http://localhost:7365/mcp")
+
+    def test_get_mcp_tools_from_string_routes_https_urls(self):
+        """Test that _get_mcp_tools_from_string still routes https:// URLs correctly."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+        )
+        
+        sentinel_tools = [MagicMock()]
+        
+        with patch.object(agent, '_get_external_mcp_tools', return_value=sentinel_tools) as mock_external:
+            result = agent._get_mcp_tools_from_string("https://api.example.com/mcp")
+            
+            assert result == sentinel_tools
+            mock_external.assert_called_once_with("https://api.example.com/mcp")
+
+
+class TestMCPServerHTTPConfig:
+    """Test MCPServerHTTP configuration with HTTP URLs."""
+
+    def test_mcp_server_http_accepts_http_url(self):
+        """Test that MCPServerHTTP accepts http:// URLs (prevent regression)."""
+        config = MCPServerHTTP(url="http://localhost:8000/mcp")
+        assert config.url == "http://localhost:8000/mcp"
+
+    def test_mcp_server_http_accepts_https_url(self):
+        """Test that MCPServerHTTP still accepts https:// URLs."""
+        config = MCPServerHTTP(url="https://api.example.com/mcp")
+        assert config.url == "https://api.example.com/mcp"
+
+    def test_agent_with_http_mcp_server_config(self):
+        """Test that Agent accepts MCPServerHTTP with http:// URL."""
+        http_config = MCPServerHTTP(url="http://localhost:8000/mcp")
+        
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+            mcps=[http_config],
+        )
+        
+        assert agent.mcps == [http_config]
+
+
+class TestHTTPMCPFragmentFiltering:
+    """Test fragment filtering for HTTP MCP URLs."""
+
+    def test_http_url_with_fragment_filters_correctly(self):
+        """Test that http:// URL with #tool fragment filters correctly."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+        )
+        
+        mock_schemas = {
+            "tool1": {"description": "Tool 1"},
+            "tool2": {"description": "Tool 2"},
+            "specific_tool": {"description": "Specific Tool"},
+        }
+        
+        with patch.object(agent, '_get_mcp_tool_schemas', return_value=mock_schemas):
+            with patch('crewai.tools.mcp_tool_wrapper.MCPToolWrapper') as mock_wrapper_class:
+                mock_tool = MagicMock()
+                mock_wrapper_class.return_value = mock_tool
+                
+                result = agent._get_external_mcp_tools("http://localhost:7365/mcp#specific_tool")
+                
+                mock_wrapper_class.assert_called_once()
+                call_args = mock_wrapper_class.call_args
+                assert call_args.kwargs['tool_name'] == 'specific_tool'
+                
+                assert len(result) == 1
+                assert result[0] == mock_tool
+
+
+class TestHTTPMCPWarningLog:
+    """Test warning log for HTTP MCP URLs."""
+
+    def test_warning_log_emitted_for_http_url(self):
+        """Test that warning log is emitted when http:// is used."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+            verbose=True,
+        )
+        
+        log_calls = []
+        logger_class = type(agent._logger)
+        original_log = logger_class.log
+        
+        def mock_log(self, level, message):
+            log_calls.append((level, message))
+            return original_log(self, level, message)
+        
+        with patch.object(logger_class, 'log', new=mock_log):
+            with patch.object(agent, '_get_mcp_tool_schemas', return_value={}):
+                agent._get_external_mcp_tools("http://localhost:7365/mcp")
+                
+                warning_messages = [msg for level, msg in log_calls if level == "warning"]
+                assert any("http://" in msg for msg in warning_messages)
+                assert any("local development" in msg for msg in warning_messages)
+                assert any("https://" in msg for msg in warning_messages)
+
+    def test_no_warning_log_for_https_url(self):
+        """Test that no warning log is emitted for https:// URLs."""
+        agent = Agent(
+            role="Test Agent",
+            goal="Test goal",
+            backstory="Test backstory",
+            verbose=True,
+        )
+        
+        log_calls = []
+        logger_class = type(agent._logger)
+        original_log = logger_class.log
+        
+        def mock_log(self, level, message):
+            log_calls.append((level, message))
+            return original_log(self, level, message)
+        
+        with patch.object(logger_class, 'log', new=mock_log):
+            with patch.object(agent, '_get_mcp_tool_schemas', return_value={}):
+                agent._get_external_mcp_tools("https://api.example.com/mcp")
+                
+                warning_messages = [msg for level, msg in log_calls if level == "warning"]
+                assert not any("http://" in msg and "local development" in msg for msg in warning_messages)

lib/crewai/tests/test_llm.py

@@ -710,7 +710,7 @@ def test_native_provider_raises_error_when_supported_but_fails():
             mock_get_native.return_value = mock_provider
 
             with pytest.raises(ImportError) as excinfo:
-                LLM(model="openai/gpt-4", is_litellm=False)
+                LLM(model="gpt-4", is_litellm=False)
 
             assert "Error importing native provider" in str(excinfo.value)
             assert "Native provider initialization failed" in str(excinfo.value)
@@ -725,3 +725,113 @@ def test_native_provider_falls_back_to_litellm_when_not_in_supported_list():
         # Should fall back to LiteLLM
         assert llm.is_litellm is True
         assert llm.model == "groq/llama-3.1-70b-versatile"
+
+
+def test_prefixed_models_with_valid_constants_use_native_sdk():
+    """Test that models with native provider prefixes use native SDK when model is in constants."""
+    # Test openai/ prefix with actual OpenAI model in constants → Native SDK
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
+        llm = LLM(model="openai/gpt-4o", is_litellm=False)
+        assert llm.is_litellm is False
+        assert llm.provider == "openai"
+
+    # Test anthropic/ prefix with Claude model in constants → Native SDK
+    with patch.dict(os.environ, {"ANTHROPIC_API_KEY": "test-key"}):
+        llm2 = LLM(model="anthropic/claude-opus-4-0", is_litellm=False)
+        assert llm2.is_litellm is False
+        assert llm2.provider == "anthropic"
+
+    # Test gemini/ prefix with Gemini model in constants → Native SDK
+    with patch.dict(os.environ, {"GOOGLE_API_KEY": "test-key"}):
+        llm3 = LLM(model="gemini/gemini-2.5-pro", is_litellm=False)
+        assert llm3.is_litellm is False
+        assert llm3.provider == "gemini"
+
+
+def test_prefixed_models_with_invalid_constants_use_litellm():
+    """Test that models with native provider prefixes use LiteLLM when model is NOT in constants."""
+    # Test openai/ prefix with non-OpenAI model (not in OPENAI_MODELS) → LiteLLM
+    llm = LLM(model="openai/gemini-2.5-flash", is_litellm=False)
+    assert llm.is_litellm is True
+    assert llm.model == "openai/gemini-2.5-flash"
+
+    # Test openai/ prefix with unknown future model → LiteLLM
+    llm2 = LLM(model="openai/gpt-future-6", is_litellm=False)
+    assert llm2.is_litellm is True
+    assert llm2.model == "openai/gpt-future-6"
+
+    # Test anthropic/ prefix with non-Anthropic model → LiteLLM
+    llm3 = LLM(model="anthropic/gpt-4o", is_litellm=False)
+    assert llm3.is_litellm is True
+    assert llm3.model == "anthropic/gpt-4o"
+
+
+def test_prefixed_models_with_non_native_providers_use_litellm():
+    """Test that models with non-native provider prefixes always use LiteLLM."""
+    # Test groq/ prefix (not a native provider) → LiteLLM
+    llm = LLM(model="groq/llama-3.3-70b", is_litellm=False)
+    assert llm.is_litellm is True
+    assert llm.model == "groq/llama-3.3-70b"
+
+    # Test together/ prefix (not a native provider) → LiteLLM
+    llm2 = LLM(model="together/qwen-2.5-72b", is_litellm=False)
+    assert llm2.is_litellm is True
+    assert llm2.model == "together/qwen-2.5-72b"
+
+
+def test_unprefixed_models_use_native_sdk():
+    """Test that unprefixed models use native SDK when model is in constants."""
+    # gpt-4o is in OPENAI_MODELS → Native OpenAI SDK
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
+        llm = LLM(model="gpt-4o", is_litellm=False)
+        assert llm.is_litellm is False
+        assert llm.provider == "openai"
+
+    # claude-opus-4-0 is in ANTHROPIC_MODELS → Native Anthropic SDK
+    with patch.dict(os.environ, {"ANTHROPIC_API_KEY": "test-key"}):
+        llm2 = LLM(model="claude-opus-4-0", is_litellm=False)
+        assert llm2.is_litellm is False
+        assert llm2.provider == "anthropic"
+
+    # gemini-2.5-pro is in GEMINI_MODELS → Native Gemini SDK
+    with patch.dict(os.environ, {"GOOGLE_API_KEY": "test-key"}):
+        llm3 = LLM(model="gemini-2.5-pro", is_litellm=False)
+        assert llm3.is_litellm is False
+        assert llm3.provider == "gemini"
+
+
+def test_explicit_provider_kwarg_takes_priority():
+    """Test that explicit provider kwarg takes priority over model name inference."""
+    # Explicit provider=openai should use OpenAI even if model name suggests otherwise
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
+        llm = LLM(model="gpt-4o", provider="openai", is_litellm=False)
+        assert llm.is_litellm is False
+        assert llm.provider == "openai"
+
+    # Explicit provider for a model with "/" should still use that provider
+    with patch.dict(os.environ, {"OPENAI_API_KEY": "test-key"}):
+        llm2 = LLM(model="gpt-4o", provider="openai", is_litellm=False)
+        assert llm2.is_litellm is False
+        assert llm2.provider == "openai"
+
+
+def test_validate_model_in_constants():
+    """Test the _validate_model_in_constants method."""
+    # OpenAI models
+    assert LLM._validate_model_in_constants("gpt-4o", "openai") is True
+    assert LLM._validate_model_in_constants("gpt-future-6", "openai") is False
+
+    # Anthropic models
+    assert LLM._validate_model_in_constants("claude-opus-4-0", "claude") is True
+    assert LLM._validate_model_in_constants("claude-future-5", "claude") is False
+
+    # Gemini models
+    assert LLM._validate_model_in_constants("gemini-2.5-pro", "gemini") is True
+    assert LLM._validate_model_in_constants("gemini-future", "gemini") is False
+
+    # Azure models
+    assert LLM._validate_model_in_constants("gpt-4o", "azure") is True
+    assert LLM._validate_model_in_constants("gpt-35-turbo", "azure") is True
+
+    # Bedrock models
+    assert LLM._validate_model_in_constants("anthropic.claude-opus-4-1-20250805-v1:0", "bedrock") is True

lib/devtools/src/crewai_devtools/__init__.py

@@ -1,3 +1,3 @@
 """CrewAI development tools."""
 
-__version__ = "1.4.0"
+__version__ = "1.4.1"