Turn schema drift into context your agents can trust.
AZ Data watches your Snowflake warehouse in real time, publishes always-current docs to your own Git repo, and hands AI agents structured context — never raw table access.
No Marketplace listing required · Works with GitHub, Bitbucket, S3, and Confluence · MCP-native
Built for teams operating at this scale
What AZ Data does
One real-time layer. Three jobs done.
Track every DDL change, publish it where your team already looks, and serve it to agents in a form they can act on safely.
Track
Hash-diff INFORMATION_SCHEMA every 1–5 minutes. Catch renames, drops, and type changes before anyone queries stale docs.
Real-time schema trackingPublish
Markdown, OKF, and a graph — committed to your repo with a real history. Documentation becomes a diff you can review, not a wiki nobody updates.
Git-native publishingServe
An MCP server gives Claude, Cursor, and your own agents structured, business-annotated context — with zero direct warehouse queries.
Agents & MCPBuilt for the agent era
Stale context is worse than no context.
An agent with no schema asks a question. An agent with a stale schema answers confidently — and wrongly. AZ Data closes that gap by design.
Why it's different
A context layer, not another catalog.
Catalogs answer "what tables exist" for humans, on a schedule measured in hours. Agents need to know "can I act on this table right now." That takes freshness in minutes, a machine-readable format, and business meaning — not just column names.
- Polls INFORMATION_SCHEMA, which has no replication lag — not ACCOUNT_USAGE
- Every read carries a last-synced timestamp, so freshness is verifiable
- Business annotations travel with the schema into Git and MCP
Extensibility
Works with the tools you already run.
Read from Snowflake. Write to your Git host. Serve any MCP-capable client. Nothing to migrate. We use Claude to enhance the platform itself — from change explanations to the annotations agents read.
Solutions
What teams use it for.
Agent grounding
Give LLM agents accurate, fresh schema context without a warehouse connection.
Schema change alerts
Know about renames and drops in minutes — as a commit, not a Slack rumor.
Audit trail
Every DDL change, with when and what, in Git history you can hand to an auditor.
Onboarding docs
New engineers read docs that were regenerated this morning, not last quarter.
Migration tracking
Watch schemas converge during a replatform, with a diff for every step.
Pipeline context
Let dbt and Airflow reviewers see the upstream schema change in the same PR.
Give your agents a warehouse they can trust.
Thirty minutes on a call, against a real Snowflake account if you'd like. Leave with a scoped pilot plan.