Traces
Audit trails and chain-of-thought traceability for agent operations
Traces provide end-to-end observability into your agents' data operations. Meko collects traces for the complete turn, all the way from user prompt, chain of thought, Meko MCP tool invocations, the underlying api calls, sql executions, and results retrieved giving you the explainability that production AI applications require.
What's traced
Meko captures:
- Data operations. Which memory, knowledge, and database operations each agent performed.
- Latencies. Timing at each stage of the pipeline (embedding, search, retrieval, etc.).
- Token costs. Per-interaction token usage for LLM calls.
- LLM reasoning. The chain of thought and reasoning traces from agent interactions.
- Execution logs. Detailed logs of MCP tool invocations and their results.
Chain-of-thought traceability
One of Meko's four pillars is Full Chain-of-Thought Traceability. This means you can:
- Debug performance issues. See exactly where time is spent in the data pipeline.
- Optimize costs. Identify which operations consume the most tokens.
- Explain agent behavior. Trace back from an agent's output to the data operations and reasoning that produced it.
- Audit compliance. Maintain a complete record of what data agents accessed and how they used it.