get_run

Get information about a specific job run with parameters: run_id (string, required), include_history (boolean, optional)

SERVERDatabricks MCP Server SOURCEandresgarciasobrado91/databricks-mcp-server

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/andresgarciasobrado91-databricks-mcp-server/get-run.md

WHAT IT DOES

What get_run does on Databricks MCP Server

AI agents call get_run 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 get_run is rated Low

This tool retrieves metadata and history about a completed or in-progress job run. It performs a read-only query operation without creating, modifying, deleting, executing code, or moving money. The blast radius of misuse is minimal—an agent could retrieve sensitive job information but cannot alter system state or resources.

From the tool's definition Tool name 'get_run' and description 'Get information about a specific job run' indicate data retrieval with no modification or side effects. The parameters (run_id and optional include_history) are for querying/filtering only.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs get_run 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 get_run, this is the rule to start with:

get_run Allowed

get_run 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": {
    "get_run": {}
  }
}

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 get_run call is checked against it from then on.

FAQ

Questions about get_run

What does the get_run tool do? +

Get information about a specific job run with parameters: run_id (string, required), include_history (boolean, optional). 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_run? +

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

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

Can I rate-limit get_run? +

Yes. Add a rate_limit block to the get_run 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_run completely? +

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

get_run is provided by the Databricks MCP Server MCP server (andresgarciasobrado91/databricks-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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