Get data quality monitoring results.
AI agents call get_data_quality_results 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.
This tool retrieves monitoring results without modifying, executing code, deleting, or moving money. It has minimal blast radius if misused—an agent could retrieve data quality results it shouldn't access, but cannot cause operational damage or irreversible changes. Classify as Read with low severity.
From the tool's definition Tool name 'get_data_quality_results' and description 'Get data quality monitoring results' indicate a retrieval operation. The verb 'get' and the absence of any modification, deletion, or execution language confirm this is a read-only query.
Documented attack patterns abuse exactly the kind of access get_data_quality_results gives an agent:
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 get_data_quality_results:
{
"version": "1",
"default": "deny",
"tools": {
"get_data_quality_results": {}
}
}get_data_quality_results is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get data quality monitoring results. It is categorised as a Read tool in the Databricks MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for get_data_quality_results: 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.
get_data_quality_results is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_data_quality_results 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.
Set action: deny in the PolicyLayer policy for get_data_quality_results. 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.
get_data_quality_results 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.
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.