get_governance_rule

THE RISK

Low Risk

Why get_governance_rule needs a policy

This tool retrieves information about an existing governance rule without modifying, executing, or deleting any data. It is a straightforward read/query operation that poses minimal security risk if misused by an AI agent, as it only returns governance metadata.

From the tool's definition Tool name is 'get_governance_rule' and description states 'Get details of a specific governance rule' — 'get' and 'details' are read operations with no side effects.

Documented attack patterns abuse exactly the kind of access get_governance_rule gives an agent:

POLICY

How to control get_governance_rule

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 get_governance_rule:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_governance_rule": {}
  }
}

get_governance_rule is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register Databricks MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Databricks MCP Server tools

Destructive delete_dbfs_path Delete a file or directory from DBFS. Destructive delete_governance_rule Delete a governance rule. Destructive delete_job Delete a job from the Databricks workspace. Destructive delete_pipeline Delete a DLT pipeline. Destructive delete_sql_warehouse Delete a SQL warehouse. Execute cancel_job_run Cancel a running job run. Execute cancel_query Cancel a running query. Execute cancel_statement Cancel statement execution.

All 86 Databricks MCP Server tools →

Read tools on other servers

M-Team MCP Server get_torrent_detail YouTube MCP Server search_channel Android Forensics ADB MCP Server parse_browser_history 0xarchive web3_challenge

Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about get_governance_rule

What does the get_governance_rule tool do? +

Get details of a specific governance rule. It is categorised as a Read tool in the Databricks MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_governance_rule? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for get_governance_rule: 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.

What risk level is get_governance_rule? +

get_governance_rule is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_governance_rule? +

Yes. Add a rate_limit block to the get_governance_rule 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.

How do I block get_governance_rule completely? +

Set action: deny in the PolicyLayer policy for get_governance_rule. 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.

What MCP server provides get_governance_rule? +

get_governance_rule 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.

Enforce policy on every Databricks MCP Server tool call.

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.

CHECK YOUR STACK →