Release 0.3.0

Added

• trace_id passback: Every successful response now includes a second content item with _trace_id metadata for request tracing.
• validate_inputs: serve(validate_inputs=True) enables pre-execution input validation via Executor.validate(). Invalid inputs are rejected before module execution.
• Always-on Context: Context is now always created for every tool call, enabling trace_id generation even without MCP callbacks.

Changed

• SchemaExporter integration: MCPServerFactory.build_tool() now uses apcore.schema.exporter.SchemaExporter.export_mcp() for canonical MCP annotation mapping instead of duplicating logic.
• to_strict_schema() delegation: OpenAIConverter._apply_strict_mode() now delegates to apcore.schema.strict.to_strict_schema() instead of custom recursive implementation. This adds x-* extension stripping, oneOf/anyOf/allOf recursion, $defs recursion, and alphabetically sorted required lists.
• Dependency bump: Requires apcore>=0.5.0 (was >=0.2.0).

Removed

• Custom strict mode: Removed OpenAIConverter._apply_strict_recursive() in favor of to_strict_schema().

Release 0.2.0

Added

• MCPServer: Non-blocking MCP server wrapper for framework integrations with configurable transport and async event loop management.
• serve() hooks: on_startup and on_shutdown callbacks for lifecycle management.
• Health endpoint: Built-in health check support for HTTP-based transports.
• Constants module: Centralized REGISTRY_EVENTS, ErrorCodes, and MODULE_ID_PATTERN for consistent values across adapters and listeners.
• Module ID validation: Enhanced id_normalizer.normalize() with format validation using MODULE_ID_PATTERN.
• Exported building blocks: Public API exports for MCPServerFactory, ExecutionRouter, RegistryListener, and TransportManager.

Fixed

• MCP Tool metadata: Fixed use of _meta instead of meta in MCP Tool constructor for proper internal metadata handling.

Refactored

• Circular import resolution: Moved utility functions (resolve_registry, resolve_executor) to dedicated _utils.py module to prevent circular dependencies between __init__.py and server/server.py.

Release 0.1.0

Added

• Public API: serve() to launch an MCP Server from any apcore Registry or Executor.
• Public API: to_openai_tools() to export apcore modules as OpenAI-compatible tool definitions.
• CLI: apcore-mcp command with --extensions-dir, --transport, --host, --port, --name, --version, and --log-level options.
• Three transports: stdio (default), Streamable HTTP, and SSE.
• SchemaConverter: JSON Schema conversion with $ref/$defs inlining for MCP and OpenAI compatibility.
• AnnotationMapper: Maps apcore annotations (readonly, destructive, idempotent, open_world) to MCP ToolAnnotations.
• ErrorMapper: Sanitizes apcore errors for safe client exposure — no stack traces, no internal details leaked.
• ModuleIDNormalizer: Bijective dot-to-dash conversion for OpenAI function name compatibility.
• OpenAIConverter: Full registry-to-OpenAI conversion with strict mode (Structured Outputs) and embed_annotations support.
• MCPServerFactory: Creates MCP Server instances, builds Tool objects, and registers list_tools/call_tool handlers.
• ExecutionRouter: Routes MCP tool calls to apcore Executor with error sanitization.
• TransportManager: Manages stdio, Streamable HTTP, and SSE transport lifecycle.
• RegistryListener: Thread-safe dynamic tool registration via registry.on("register"/"unregister") callbacks.
• Structured logging: All components use logging.getLogger(__name__) under the apcore_mcp namespace.
• Dual input: Both serve() and to_openai_tools() accept either a Registry or Executor instance.
• Filtering: tags and prefix parameters for selective module exposure.
• 260 tests: Unit, integration, E2E, performance, and security test suites.