AI agents use apply_uc_tags to create or update resources in Databricks MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Databricks MCP Server environment.
Applying tags modifies object metadata in a reversible manner—tags can be removed or changed later. While it affects governance and organization of Unity Catalog resources, it does not delete data, execute code, or trigger financial transactions. This qualifies as a Write operation.
From the tool's definition Tool name 'apply_uc_tags' and description 'Apply tags to Unity Catalog objects' indicate modification of metadata/tags on existing catalog objects. This is a create/update operation on object attributes.
Documented attack patterns abuse exactly the kind of access apply_uc_tags gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Databricks MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for apply_uc_tags:
{
"version": "1",
"default": "deny",
"tools": {
"apply_uc_tags": {
"limits": [
{
"counter": "apply_uc_tags_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}apply_uc_tags stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Apply tags to Unity Catalog objects. It is categorised as a Write tool in the Databricks MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for apply_uc_tags: 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 Databricks MCP Server. Nothing to install.
apply_uc_tags 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 apply_uc_tags 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 apply_uc_tags. 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.
apply_uc_tags is provided by the Databricks MCP Server MCP server (pulkitxchadha/awesome-databricks-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Databricks MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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86 Databricks MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.