MCP Test MCP

--- story_id: "0002" title: "Define Pydantic data models" created: "2025-10-09" status: done dependencies: ["0001"] estimated_complexity: "low" tags: ["models", "data-validation", "phase1"] - status: in-progress timestamp: 2025-10-09T20:31:21Z - status: ready-for-review timestamp: 2025-10-09T20:40:28Z - status: done timestamp: 2025-10-09T20:52:24Z --- # Story 0002: Define Pydantic data models ## Description Create Pydantic v2 models for all data structures used in mcp-test-mcp, including connection state, tool responses, error responses, and metadata structures. ## Acceptance Criteria - [x] `src/mcp_test_mcp/models.py` created - [x] `ConnectionState` model defined with all required fields - [x] `ToolResponse` model defined with success, connection, tools, metadata - [x] `ToolCallResponse` model defined with execution details - [x] `ResourceResponse` model defined for resource operations - [x] `PromptResponse` model defined for prompt operations - [x] `ErrorResponse` model defined with type, message, details, suggestion - [x] All models use proper Pydantic v2 syntax - [x] Models include field descriptions and validation rules - [x] Unit tests for model validation created ## Technical Notes **Key models from proposal:** ```python class ConnectionState(BaseModel): server_url: str transport: str # "streaming-http" | "stdio" connected_at: datetime server_info: dict statistics: dict class ErrorResponse(BaseModel): success: Literal[False] error: dict # {type, message, details, suggestion} connection: Optional[dict] metadata: dict ``` **Error types to support:** - not_connected - connection_failed - tool_not_found - resource_not_found - prompt_not_found - invalid_arguments - execution_error - timeout - transport_error ## AI Directives **IMPORTANT**: As you work through this story, please mark checklist items as complete `[x]` as you finish them. This ensures that if we need to pause and resume work, we have a clear record of progress. Update the `status` field in the frontmatter when moving between stages (in-progress, ready-for-review, done, blocked). Use Pydantic v2 syntax (not v1). Search for current Pydantic v2 best practices if needed. ## Implementation Notes **Implementation completed on 2025-10-09** ### Files Created - `src/mcp_test_mcp/models.py` - All Pydantic v2 models with comprehensive field descriptions - `tests/test_models.py` - 25 comprehensive tests with 100% coverage on models ### Models Implemented 1. **ConnectionState** - Tracks server connection state with URL, transport type, connection timestamp, server info, and usage statistics 2. **ToolResponse** - Response from tool discovery/listing operations 3. **ToolCallResponse** - Response from tool execution with timing and results 4. **ResourceResponse** - Response from resource list/read operations 5. **PromptResponse** - Response from prompt list/execute operations 6. **ErrorDetail** - Structured error information with categorized error types 7. **ErrorResponse** - Error response wrapper with connection state and metadata ### Key Features - All models use Pydantic v2 syntax with `Field()` for descriptions - Comprehensive field-level documentation for API clarity - Proper type hints including `Optional`, `Literal`, and dict typing - Default values for optional fields and factory functions for mutable defaults - Support for all 9 error types defined in requirements - Full validation on required fields, literal types, and nested models ### Testing - 25 test cases covering: - Valid model creation with minimal and full fields - Field validation (required fields, type checking, literal values) - Error response handling for all error types - Model serialization/deserialization (round-trip testing) - All tests pass with 100% code coverage on models.py - Linting passes: black, ruff, mypy all clean ### Pydantic v2 Best Practices Applied - Used `Field()` with descriptions for all fields - Used `model_dump()` instead of v1's `dict()` - Proper ConfigDict usage patterns researched via context7 - Type-safe Literal types for constrained string values - Optional fields properly typed with `Optional[T]` - Factory functions (`default_factory`) for mutable defaults