Observability
Traces, conversation history, and chain-of-thought visibility
Meko provides end-to-end observability into your agents' data operations, giving you the visibility production AI applications require.
What you can observe
Traces
Every data operation your agent performs is traced:
- Memory operations - When memories are added, searched, or cleared.
- Knowledge base queries - Document retrieval operations and their results.
- Database operations - SQL queries and their execution times.
- MCP tool invocations - Each tool call and its result.
Conversation history
Meko stores the full conversation history between users and agents:
- Verbatim message logs (user + assistant)
- Timestamps and session identifiers
- S3-backed tiering for cost-effective long-term storage
Chain of thought
For agents that produce reasoning traces, Meko captures the complete chain of thought:
- Step-by-step reasoning logs
- Sub-agent orchestration audit trails
- Decision points and the data that informed them
Key metrics
For each datapack, you can view:
- Number of memories stored
- Number of knowledge base sources (or document count)
- Number of MCP requests (past day / week / month)
- Token costs per interaction
- Latency at each pipeline stage
LangFuse integration
Meko integrates with LangFuse for trace collection and visualization.