databricks_search_experiments

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-search-experiments.md

WHAT IT DOES

What databricks_search_experiments does on Databricks MCP Server

AI agents call databricks_search_experiments 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_search_experiments is rated Low

The verb 'search' combined with 'experiments' (a read-only MLflow concept in Databricks) suggests this tool queries experiment metadata. No indication of modification, deletion, execution, or financial impact. Classified as Read due to its search/query nature, though the empty description reduces confidence slightly.

From the tool's definition Tool name 'search_experiments' indicates a query/search operation, which typically retrieves data without side effects. The description is empty, limiting evidence quality.

Attacks that exploit this kind of access

RECOMMENDED RULE

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

databricks_search_experiments Allowed

databricks_search_experiments 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_search_experiments": {}
  }
}

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_search_experiments call is checked against it from then on.

FAQ

Questions about databricks_search_experiments

What does the databricks_search_experiments tool do? +

databricks_search_experiments 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_search_experiments? +

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

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

Can I rate-limit databricks_search_experiments? +

Yes. Add a rate_limit block to the databricks_search_experiments 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_search_experiments completely? +

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

databricks_search_experiments 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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