1. Automated Morning Briefings
The nightly scheduler (SCHEDULER_ENABLED=true) triggers an automated evaluation loop at 02:00 local time:
- Daily Ingestion & Mart Build: Executes datastream pulls and runs dbt models to update canonical marts.
- Quality & Anomaly Checks: Evaluates data freshness, volume checks, and z-score anomaly detectors.
- Briefing Synthesis: Compiles daily KPI deltas, flagged anomalies, and active business context into a structured morning briefing.
get_morning_briefing(project_id).
2. Business Context Events
Marketing performance fluctuations rarely occur in a vacuum. toorow allows teams to register Context Events (e.g., website redesigns, PR announcements, price changes, ad campaign launches). When an agent analyzes metric anomalies, toorow correlates performance shifts against registered context events, providing instant explanatory context (e.g., “Conversions dropped 25% on July 14, coinciding with a scheduled checkout gateway migration”).3. FastMCP Dual-Channel Response Model
Every MCP data tool in toorow enforces a dual-channel output model (AD-1):- Text Channel: A concise, structured narrative text summary (≤ 30 lines) optimized for insertion directly into the LLM context window.
- Structured Content Channel (
structuredContent): A complete JSON envelope containing raw metric arrays, data provenance, freshness timestamps, and quality alerts, rendered visually by MCP App widgets in compatible host interfaces.
Next Steps & Cross-References
Semantic Layer
Review canonical marts and ratio calculations supporting agent queries.
Anomaly Detection
Understand z-score thresholds and severity levels for anomaly alerts.
Security Constraints
Examine FastMCP dual-channel response rules and AD-5 tenant isolation.
Quickstart Guide
Test MCP tool responses locally with the FastMCP dev server.