databricks_get_job

Get detailed information about a specific job.

SERVERDatabricks MCP Server SOURCEpypi:databricks-sdk-mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-get-job.md

WHAT IT DOES

What databricks_get_job does on Databricks MCP Server

AI agents call databricks_get_job to retrieve information from Databricks MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why databricks_get_job is rated Low

This tool retrieves metadata and status information about an existing job. The verb 'get' and the stated purpose of obtaining 'detailed information' confirm this is a read-only query operation. No modifications, deletions, or external executions are performed. The blast radius of misuse is minimal—an attacker could enumerate jobs but cannot alter or trigger them.

From the tool's definition Tool name 'databricks_get_job' and description 'Get detailed information about a specific job' indicate a retrieval operation with no side effects.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs databricks_get_job safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Databricks MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For databricks_get_job, this is the rule to start with:

databricks_get_job Allowed

databricks_get_job is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

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

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Databricks MCP Server, apply this rule, and every databricks_get_job call is checked against it from then on.

FAQ

Questions about databricks_get_job

What does the databricks_get_job tool do? +

Get detailed information about a specific job. 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 databricks_get_job? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_get_job: 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 databricks_get_job? +

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

Can I rate-limit databricks_get_job? +

Yes. Add a rate_limit block to the databricks_get_job 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 databricks_get_job completely? +

Set action: deny in the PolicyLayer policy for databricks_get_job. 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 databricks_get_job? +

databricks_get_job is provided by the Databricks MCP Server MCP server (pypi:databricks-sdk-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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