Migration Strategy Prover MCP Connector for Claude
A+An AI recommended a big-bang database migration over the weekend. No dependency map — 7 services read from that database. No rollback plan — 'just restore from backup.' No data validation — 2.3 million records with timezone-dependent timestamps. The migration ran Saturday at 2 AM. By 4 AM, 3 downstream services were returning stale data, the backup was 6 hours old, and 14,000 customer records had corrupted timestamps. Monday morning: 72-hour incident. This tool forces risk assessment, rollback definition, data integrity verification, cutover planning, and stakeholder alignment.
AI agents recommend migrations without mapping what breaks. They skip rollback planning. They assume data consistency. They propose big-bang cutovers. They forget 12 teams depend on the system.
The Problem
LLMs commit five migration failures that cause multi-day incidents:
- Risk Unassessed — 'Straightforward migration, no major risks.' No dependency map. No blast radius analysis. 7 services read from that database, 3 teams write to it, and the billing pipeline runs a nightly job against it. None of this was documented.
- Rollback Undefined — 'We can always restore from backup.' The backup is 6 hours old. The migration wrote 340,000 records during the window. Those records are gone. 'Just switch back' is not a rollback plan when data has been mutated.
- Data Integrity Unproven — 'Data migrates cleanly.' No row count comparison. No checksum verification. No referential integrity check. 14,000 records have timezone-corrupted timestamps because the source was UTC and the destination was America/New_York.
- Cutover Missing — 'Big bang over the weekend.' No traffic shifting. No canary percentage. No monitoring at each stage. No go/no-go criteria. The switch happened at 2 AM and the first alert fired at 4 AM — 2 hours of silent corruption.
- Stakeholders Unaligned — 'Everyone knows about the migration.' The support team found out Monday morning from customer tickets. The on-call engineer was not added to the escalation channel. The runbook was in someone's personal Notion.
How It Works
5 Decision Pivots:
- riskAssessed — Dependencies mapped, blast radius documented, failure scenarios enumerated, data volume quantified, timeline realistic.
- rollbackDefined — Trigger metrics specified, step-by-step procedure written, timeline estimated, mutated data handling planned.
- dataIntegrityProven — Row counts, checksums, referential integrity, edge cases (NULLs, unicode, timezones, precision).
- cutoverPlanned — Strategy chosen (Strangler Fig/Blue-Green/Canary), traffic shifting percentages, monitoring at each stage, go/no-go gates.
- stakeholdersAligned — All affected teams listed, customer notification if needed, shared timeline, escalation paths, published runbook.
The Verdict Matrix
| First Failing Pivot | Verdict | Meaning |
|---|---|---|
| riskAssessed = false | RISK_UNASSESSED | No dependency map. No blast radius. |
| rollbackDefined = false | ROLLBACK_UNDEFINED | 'Just switch back' is not a plan. |
| dataIntegrityProven = false | DATA_INTEGRITY_UNPROVEN | Assumed consistency. No validation. |
| cutoverPlanned = false | CUTOVER_MISSING | Big bang. No monitoring. No gates. |
| stakeholdersAligned = false | STAKEHOLDERS_UNALIGNED | Support found out from customer tickets. |
| All pivots pass | MIGRATION_PROVEN | Mapped, planned, verified, monitored, communicated. |
Why It Works
- Tool calls are obligations. The agent cannot recommend a migration without mapping dependencies, defining rollback triggers, specifying data validation criteria, and listing affected teams.
- Consistency engine catches contradictions. If the agent claims
rollbackDefined=truebut says 'restore from backup,' the engine rejects with specific rollback procedure coaching. - Semantic traps detect hand-waving. 'No major risks,' 'just switch back,' 'data will be consistent,' 'big bang cutover,' and 'everyone knows' trigger automatic rejection.
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