Merge pull request #177 from prane-eth/feat/mcp-resources-prompts

Feature: Added support for MCP resources and prompts

Author: KennyVaneetvelde

atomic-agents/atomic_agents/base/__init__.py

@@ -2,9 +2,15 @@
 
 from .base_io_schema import BaseIOSchema
 from .base_tool import BaseTool, BaseToolConfig
+from .base_resource import BaseResource, BaseResourceConfig
+from .base_prompt import BasePrompt, BasePromptConfig
 
 __all__ = [
     "BaseIOSchema",
     "BaseTool",
     "BaseToolConfig",
+    "BaseResource",
+    "BaseResourceConfig",
+    "BasePrompt",
+    "BasePromptConfig",
 ]

atomic-agents/atomic_agents/base/base_prompt.py

@@ -0,0 +1,141 @@
+from typing import Optional, Type, get_args, get_origin
+from abc import ABC, abstractmethod
+from pydantic import BaseModel
+
+from atomic_agents.base.base_io_schema import BaseIOSchema
+
+
+class BasePromptConfig(BaseModel):
+    """
+    Configuration for a prompt.
+
+    Attributes:
+        title (Optional[str]): Overrides the default title of the prompt.
+        description (Optional[str]): Overrides the default description of the prompt.
+    """
+
+    title: Optional[str] = None
+    description: Optional[str] = None
+
+
+class BasePrompt[InputSchema: BaseIOSchema, OutputSchema: BaseIOSchema](ABC):
+    """
+    Base class for prompts within the Atomic Agents framework.
+
+    Prompts enable agents to perform specific tasks by providing a standardized interface
+    for input and output. Each prompt is defined with specific input and output schemas
+    that enforce type safety and provide documentation.
+
+    Type Parameters:
+        InputSchema: Schema defining the input data, must be a subclass of BaseIOSchema.
+        OutputSchema: Schema defining the output data, must be a subclass of BaseIOSchema.
+
+    Attributes:
+        config (BasePromptConfig): Configuration for the prompt, including optional title and description overrides.
+        input_schema (Type[InputSchema]): Schema class defining the input data (derived from generic type parameter).
+        output_schema (Type[OutputSchema]): Schema class defining the output data (derived from generic type parameter).
+        prompt_name (str): The name of the prompt, derived from the input schema's title or overridden by the config.
+        prompt_description (str): Description of the prompt, derived from the input schema's description or overridden by the config.
+    """
+
+    def __init__(self, config: BasePromptConfig = BasePromptConfig()):
+        """
+        Initializes the BasePrompt with an optional configuration override.
+
+        Args:
+            config (BasePromptConfig, optional): Configuration for the prompt, including optional title and description overrides.
+        """
+        self.config = config
+
+    def __init_subclass__(cls, **kwargs):
+        """
+        Hook called when a class is subclassed.
+
+        Captures generic type parameters during class creation and stores them as class attributes
+        to work around the unreliable __orig_class__ attribute in modern Python generic syntax.
+        """
+        super().__init_subclass__(**kwargs)
+        if hasattr(cls, "__orig_bases__"):
+            for base in cls.__orig_bases__:
+                if get_origin(base) is BasePrompt:
+                    args = get_args(base)
+                    if len(args) == 2:
+                        cls._input_schema_cls = args[0]
+                        cls._output_schema_cls = args[1]
+                        break
+
+    @property
+    def input_schema(self) -> Type[InputSchema]:
+        """
+        Returns the input schema class for the prompt.
+
+        Returns:
+            Type[InputSchema]: The input schema class.
+        """
+        # Inheritance pattern: MyPrompt(BasePrompt[Schema1, Schema2])
+        if hasattr(self.__class__, "_input_schema_cls"):
+            return self.__class__._input_schema_cls
+
+        # Dynamic instantiation: MockPrompt[Schema1, Schema2]()
+        if hasattr(self, "__orig_class__"):
+            TI, _ = get_args(self.__orig_class__)
+            return TI
+
+        # No type info available: MockPrompt()
+        return BaseIOSchema
+
+    @property
+    def output_schema(self) -> Type[OutputSchema]:
+        """
+        Returns the output schema class for the prompt.
+
+        Returns:
+            Type[OutputSchema]: The output schema class.
+        """
+        # Inheritance pattern: MyPrompt(BasePrompt[Schema1, Schema2])
+        if hasattr(self.__class__, "_output_schema_cls"):
+            return self.__class__._output_schema_cls
+
+        # Dynamic instantiation: MockPrompt[Schema1, Schema2]()
+        if hasattr(self, "__orig_class__"):
+            _, TO = get_args(self.__orig_class__)
+            return TO
+
+        # No type info available: MockPrompt()
+        return BaseIOSchema
+
+    @property
+    def prompt_name(self) -> str:
+        """
+        Returns the name of the prompt.
+
+        Returns:
+            str: The name of the prompt.
+        """
+        return self.config.title or self.input_schema.model_json_schema()["title"]
+
+    @property
+    def prompt_description(self) -> str:
+        """
+        Returns the description of the prompt.
+
+        Returns:
+            str: The description of the prompt.
+        """
+        return self.config.description or self.input_schema.model_json_schema()["description"]
+
+    @abstractmethod
+    def generate(self, params: InputSchema) -> OutputSchema:
+        """
+        Executes the prompt with the provided parameters.
+
+        Args:
+            params (InputSchema): Input parameters adhering to the input schema.
+
+        Returns:
+            OutputSchema: Output resulting from executing the prompt, adhering to the output schema.
+
+        Raises:
+            NotImplementedError: If the method is not implemented by a subclass.
+        """
+        pass

atomic-agents/atomic_agents/base/base_resource.py

@@ -0,0 +1,141 @@
+from typing import Optional, Type, get_args, get_origin
+from abc import ABC, abstractmethod
+from pydantic import BaseModel
+
+from atomic_agents.base.base_io_schema import BaseIOSchema
+
+
+class BaseResourceConfig(BaseModel):
+    """
+    Configuration for a resource.
+
+    Attributes:
+        title (Optional[str]): Overrides the default title of the resource.
+        description (Optional[str]): Overrides the default description of the resource.
+    """
+
+    title: Optional[str] = None
+    description: Optional[str] = None
+
+
+class BaseResource[InputSchema: BaseIOSchema, OutputSchema: BaseIOSchema](ABC):
+    """
+    Base class for resources within the Atomic Agents framework.
+
+    Resources enable agents to perform specific tasks by providing a standardized interface
+    for input and output. Each resource is defined with specific input and output schemas
+    that enforce type safety and provide documentation.
+
+    Type Parameters:
+        InputSchema: Schema defining the input data, must be a subclass of BaseIOSchema.
+        OutputSchema: Schema defining the output data, must be a subclass of BaseIOSchema.
+
+    Attributes:
+        config (BaseResourceConfig): Configuration for the resource, including optional title and description overrides.
+        input_schema (Type[InputSchema]): Schema class defining the input data (derived from generic type parameter).
+        output_schema (Type[OutputSchema]): Schema class defining the output data (derived from generic type parameter).
+        resource_name (str): The name of the resource, derived from the input schema's title or overridden by the config.
+        resource_description (str): Description of the resource, derived from the input schema's description or overridden by the config.
+    """
+
+    def __init__(self, config: BaseResourceConfig = BaseResourceConfig()):
+        """
+        Initializes the BaseResource with an optional configuration override.
+
+        Args:
+            config (BaseResourceConfig, optional): Configuration for the resource, including optional title and description overrides.
+        """
+        self.config = config
+
+    def __init_subclass__(cls, **kwargs):
+        """
+        Hook called when a class is subclassed.
+
+        Captures generic type parameters during class creation and stores them as class attributes
+        to work around the unreliable __orig_class__ attribute in modern Python generic syntax.
+        """
+        super().__init_subclass__(**kwargs)
+        if hasattr(cls, "__orig_bases__"):
+            for base in cls.__orig_bases__:
+                if get_origin(base) is BaseResource:
+                    args = get_args(base)
+                    if len(args) == 2:
+                        cls._input_schema_cls = args[0]
+                        cls._output_schema_cls = args[1]
+                        break
+
+    @property
+    def input_schema(self) -> Type[InputSchema]:
+        """
+        Returns the input schema class for the resource.
+
+        Returns:
+            Type[InputSchema]: The input schema class.
+        """
+        # Inheritance pattern: MyResource(BaseResource[Schema1, Schema2])
+        if hasattr(self.__class__, "_input_schema_cls"):
+            return self.__class__._input_schema_cls
+
+        # Dynamic instantiation: MockResource[Schema1, Schema2]()
+        if hasattr(self, "__orig_class__"):
+            TI, _ = get_args(self.__orig_class__)
+            return TI
+
+        # No type info available: MockResource()
+        return BaseIOSchema
+
+    @property
+    def output_schema(self) -> Type[OutputSchema]:
+        """
+        Returns the output schema class for the resource.
+
+        Returns:
+            Type[OutputSchema]: The output schema class.
+        """
+        # Inheritance pattern: MyResource(BaseResource[Schema1, Schema2])
+        if hasattr(self.__class__, "_output_schema_cls"):
+            return self.__class__._output_schema_cls
+
+        # Dynamic instantiation: MockResource[Schema1, Schema2]()
+        if hasattr(self, "__orig_class__"):
+            _, TO = get_args(self.__orig_class__)
+            return TO
+
+        # No type info available: MockResource()
+        return BaseIOSchema
+
+    @property
+    def resource_name(self) -> str:
+        """
+        Returns the name of the resource.
+
+        Returns:
+            str: The name of the resource.
+        """
+        return self.config.title or self.input_schema.model_json_schema()["title"]
+
+    @property
+    def resource_description(self) -> str:
+        """
+        Returns the description of the resource.
+
+        Returns:
+            str: The description of the resource.
+        """
+        return self.config.description or self.input_schema.model_json_schema()["description"]
+
+    @abstractmethod
+    def read(self, params: InputSchema) -> OutputSchema:
+        """
+        Executes the resource with the provided parameters.
+
+        Args:
+            params (InputSchema): Input parameters adhering to the input schema.
+
+        Returns:
+            OutputSchema: Output resulting from executing the resource, adhering to the output schema.
+
+        Raises:
+            NotImplementedError: If the method is not implemented by a subclass.
+        """
+        pass

atomic-agents/atomic_agents/connectors/mcp/__init__.py

@@ -1,23 +1,39 @@
-from .mcp_tool_factory import (
-    MCPToolFactory,
+from .mcp_factory import (
+    MCPFactory,
     MCPToolOutputSchema,
     fetch_mcp_tools,
     fetch_mcp_tools_async,
+    fetch_mcp_resources,
+    fetch_mcp_resources_async,
+    fetch_mcp_prompts,
+    fetch_mcp_prompts_async,
     create_mcp_orchestrator_schema,
-    fetch_mcp_tools_with_schema,
+    fetch_mcp_attributes_with_schema,
 )
 from .schema_transformer import SchemaTransformer
-from .tool_definition_service import MCPTransportType, MCPToolDefinition, ToolDefinitionService
+from .mcp_definition_service import (
+    MCPTransportType,
+    MCPToolDefinition,
+    MCPResourceDefinition,
+    MCPPromptDefinition,
+    MCPDefinitionService,
+)
 
 __all__ = [
-    "MCPToolFactory",
+    "MCPFactory",
     "MCPToolOutputSchema",
     "fetch_mcp_tools",
     "fetch_mcp_tools_async",
+    "fetch_mcp_resources",
+    "fetch_mcp_resources_async",
+    "fetch_mcp_prompts",
+    "fetch_mcp_prompts_async",
     "create_mcp_orchestrator_schema",
-    "fetch_mcp_tools_with_schema",
+    "fetch_mcp_attributes_with_schema",
     "SchemaTransformer",
     "MCPTransportType",
     "MCPToolDefinition",
-    "ToolDefinitionService",
+    "MCPResourceDefinition",
+    "MCPPromptDefinition",
+    "MCPDefinitionService",
 ]