databricks_get_pipeline

A read tool on the Databricks MCP server.

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-pipeline.md

WHAT IT DOES

What databricks_get_pipeline does on Databricks MCP Server

AI agents call databricks_get_pipeline 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_pipeline is rated Low

The 'get' prefix strongly suggests a retrieval operation on pipeline metadata or state. Without a description, confidence is moderate, but the naming convention and context within a Databricks server alongside query/status tools (e.g., databricks_command_status) indicates this likely queries pipeline information. No side effects expected from reading pipeline state.

From the tool's definition Tool name 'get_pipeline' follows read-like semantics (get/fetch pattern); verb 'get' indicates retrieval rather than modification or execution.

Attacks that exploit this kind of access

RECOMMENDED RULE

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

databricks_get_pipeline Allowed

databricks_get_pipeline 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_pipeline": {}
  }
}

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_pipeline call is checked against it from then on.

FAQ

Questions about databricks_get_pipeline

What does the databricks_get_pipeline tool do? +

databricks_get_pipeline is a read tool on the Databricks MCP Server MCP server. 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_pipeline? +

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

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

Can I rate-limit databricks_get_pipeline? +

Yes. Add a rate_limit block to the databricks_get_pipeline 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_pipeline completely? +

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

databricks_get_pipeline 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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