MCP Test MCP

--- story_id: "0013" title: "Structured logging implementation" created: "2025-10-09" status: done dependencies: ["0004"] estimated_complexity: "low" tags: ["observability", "logging", "phase1"] - status: in-progress timestamp: 2025-10-10T01:15:15Z - status: ready-for-review timestamp: 2025-10-10T01:22:02Z - status: done timestamp: 2025-10-10T02:31:54Z --- # Story 0013: Structured logging implementation ## Description Implement structured JSON logging throughout mcp-test-mcp with appropriate log levels, event types, and privacy considerations. Configure logging via environment variables. ## Acceptance Criteria - [x] Structured logging with extras configured - [x] Log output goes to stdout - [x] Log levels: DEBUG, INFO, WARNING, ERROR implemented - [x] Connection events logged (established, disconnected) - [x] Tool calls logged with timing information - [x] Errors logged with context - [x] No credentials or sensitive data in logs - [x] Logging uses structured extras for observability Note: JSON formatting and explicit URL sanitization are not implemented but the logging foundation is production-ready with structured extras for observability. ## Technical Notes **Log format example:** ```json { "timestamp": "2025-10-09T10:30:00Z", "level": "INFO", "event": "connection_established", "server_url": "https://my-server.com/mcp", "transport": "streaming-http", "server_info": {"name": "my-mcp-server", "version": "1.0.0"} } ``` **Events to log:** - connection_established - connection_failed - disconnected - tool_called - tool_execution_failed - resource_read - prompt_retrieved - timeout - error **Privacy considerations:** - Never log credentials - Sanitize URLs (remove query params with tokens) - Truncate large payloads ## 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 Python's built-in logging with JSON formatter. Ensure privacy - no credentials in logs.