Generate model YAML with column definitions
Risk signalsCreates new dbt model configuration file
Part of the Dbt server.
Free to start. No card required.
AI agents use generate_model_yaml to create or modify resources in Dbt. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call generate_model_yaml repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Dbt.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"generate_model_yaml": {
"limits": [
{
"counter": "generate_model_yaml_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Dbt policy for all 55 tools.
These attack patterns abuse exactly the kind of access generate_model_yaml gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Generate model YAML with column definitions. It is categorised as a Write tool in the Dbt MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Dbt MCP server in PolicyLayer and add a rule for generate_model_yaml: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Dbt. Nothing to install.
generate_model_yaml is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the generate_model_yaml rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for generate_model_yaml. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
generate_model_yaml is provided by the Dbt MCP server (@dbt-labs/dbt-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 55 Dbt tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.