Get permissions for a job with parameter: job_id (required)
AI agents call get_job_permissions to retrieve information from Databricks Permissions MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves permission information for a Databricks job without modifying, deleting, or executing any code. It is a read-only operation. However, severity is elevated to medium because permission data can be sensitive and reveal security posture; misuse could inform reconnaissance attacks or privilege escalation attempts on the Databricks workspace.
From the tool's definition Tool name contains 'get_' prefix and description states 'Get permissions for a job' — a read operation that retrieves permission data.
Attacks that exploit this kind of access
Get permissions for a job with parameter: job_id (required). It is categorised as a Read tool in the Databricks Permissions MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Databricks Permissions MCP Server MCP server in PolicyLayer and add a rule for get_job_permissions: 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 Permissions MCP Server. Nothing to install.
get_job_permissions is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_job_permissions 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 get_job_permissions. 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.
get_job_permissions is provided by the Databricks Permissions MCP Server MCP server (justtryai/databricks-permissions-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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