oscerd opened a new pull request, #25050: URL: https://github.com/apache/camel/pull/25050
## Summary Adds a new MCP tool `camel_runtime_ai_trace` that traces AI-specific exchange flow in running Camel applications. - **AI component detection**: identifies Bedrock, LangChain4j, Docling, Textract, OpenAI, KServe, TorchServe, DJL, HuggingFace components in running routes - **AI header extraction**: captures token usage, model IDs, guardrail outcomes, completion reasons, streaming chunk counts from exchange headers - **Processor statistics**: filters top processor stats to AI components only, showing latency (mean/max/min/last) and exchange counts - **Structured summary**: aggregates key AI metrics (token usage, model, completion reason, guardrail action) into a summary Combines data from three existing runtime queries (`get_history`, `get_top_processors`, `get_route_structure`) and filters for AI-relevant data. ## Test plan - [x] 10 unit tests covering component extraction, header categorization, processor stats, scheme parsing, and edge cases - [x] All 309 existing MCP server tests pass (no regressions) _Claude Code on behalf of oscerd_ 🤖 Generated with [Claude Code](https://claude.com/claude-code) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
