Low Risk

list_job_runs

List job runs, either all runs or runs for a specific job.

How to control list_job_runs ↓

What list_job_runs does on Databricks MCP Server

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

Low Risk

Why list_job_runs needs a policy

This tool retrieves information about job runs without creating, modifying, deleting, or executing any operations. It is a pure read operation that queries existing job run metadata from the Databricks workspace. The blast radius of misuse is minimal—an attacker could only gain visibility into job history, not alter systems or trigger actions.

From the tool's definition Tool name 'list_job_runs' and description 'List job runs, either all runs or runs for a specific job' indicates a query/retrieval operation with no data modification or execution.

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

How to control list_job_runs

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 list_job_runs:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "list_job_runs": {}
  }
}

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

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

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Questions about list_job_runs

What does the list_job_runs tool do? +

List job runs, either all runs or runs for 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 list_job_runs? +

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

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

Can I rate-limit list_job_runs? +

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

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

list_job_runs 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.

Free to start. No card required.

86 Databricks MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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