get_job_permissions

Get permissions for a job with parameter: job_id (required)

Server Databricks Permissions MCP Server justtryai/databricks-permissions-mcp-server
Category Read
Risk class Low
Parameters 00 required

What get_job_permissions does on Databricks Permissions MCP Server

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.

Why get_job_permissions needs a policy

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.

Questions about get_job_permissions

What does the get_job_permissions tool do? +

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.

How do I enforce a policy on get_job_permissions? +

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.

What risk level is get_job_permissions? +

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

Can I rate-limit get_job_permissions? +

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.

How do I block get_job_permissions completely? +

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.

What MCP server provides get_job_permissions? +

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.

// LOOK UP ANOTHER 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.

Teams ship this data inside their own products. See what a licence covers →

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.