MCP Data Layer for product teams

A single MCP server that exposes the warehouse + product DB + key SaaS APIs (CRM, billing, helpdesk) to any agent the team uses. PMs test hypotheses in Cursor / Claude Code without filing tickets to data engineering: "what's the 7-day retention of users who hit the new pricing page?" gets answered directly.

At a payments group, the bottleneck on product velocity was not engineering — it was PMs queueing for analyst time. The MCP data layer was estimated at 5–10× speedup on hypothesis testing for the product organization. Cheap to build, compounds across every PM and every agent.

1. Stand up an MCP server (Python or TypeScript) with one tool per data source: query_warehouse, query_crm, query_helpdesk.
2. Use a read-only DB role. Never expose write tools through this layer.
3. Add per-user audit logging. Every query stamped with caller identity, redacted on PII columns.
4. Document each tool in the MCP manifest with example queries — agents pick them up automatically.
5. Distribute via the team's CLAUDE.md / AGENTS.md so every project inherits access.
6. Add row-level security on the warehouse for any table with customer data — the MCP layer trusts the database to enforce ACLs.
7. Run a 2-PM pilot for a week; expand once query patterns stabilize.

• PII leakage through ad-hoc queries is the realistic failure mode. Enforce column-level redaction at the DB role and never let the MCP layer become the trust boundary.