# Turn Your dbt Project Into a Semantic Layer for Agents

> Turn dbt into a semantic layer for agents: go from models and a manifest to governed metrics agents can query and chart consistently, without rebuilding your stack.

> Draft placeholder. Full article coming soon.

You already have dbt models, tests, and a manifest. This post will show how to turn that into a governed semantic layer agents can query, without rebuilding your stack.

## What this will cover

- Reading your dbt manifest to bootstrap metrics and relationships
- Defining metrics once so every consumer gets the same number
- Tagging the tenant key that scopes each customer's rows
- Exposing governed metrics to agents over MCP
- Charting the agent's query results in Claude or ChatGPT with [`@bonnard/mcp-charts`](https://www.npmjs.com/package/@bonnard/mcp-charts)

## Frequently asked questions

**Do I need to migrate off dbt?**

No. A semantic layer reads your existing dbt models. You keep dbt as your transformation layer.

**What if I only have models, not a semantic layer?**

That's the common case. You bootstrap from the manifest and define metrics on top.

**How do agents chart the results?**

Add a `visualize` tool to your MCP server with `@bonnard/mcp-charts`. The agent queries a metric, your `runSql` returns the rows, and an interactive chart renders in Claude or ChatGPT. Bonnard never touches your database. See the [MCP Charts guide](/blog/mcp-charts).