query_dataapi · Cloudera Data Visualization MCP Server MCP

WHAT IT DOES

What query_dataapi does on Cloudera Data Visualization MCP Server

AI agents invoke query_dataapi to trigger actions in Cloudera Data Visualization MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why query_dataapi needs a policy

The name 'query_dataapi' suggests executing queries against a data API. In the context of Cloudera Data Visualization, this likely runs queries against datasets or connections, which constitutes an Execute action (running queries with effects that depend on arguments). However, the empty description significantly lowers confidence.

From the tool's definition Tool name 'query_dataapi' — description is empty and uninformative

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

query_dataapi Rate-limited

query_dataapi stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "query_dataapi": {
      "limits": [
        {
          "counter": "query_dataapi_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Cloudera Data Visualization MCP Server, so you can run agents against it safely.

FAQ

Questions about query_dataapi

What does the query_dataapi tool do? +

query_dataapi. It is categorised as a Execute tool in the Cloudera Data Visualization MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on query_dataapi? +

Register the Cloudera Data Visualization MCP Server MCP server in PolicyLayer and add a rule for query_dataapi: 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 Cloudera Data Visualization MCP Server. Nothing to install.

What risk level is query_dataapi? +

query_dataapi is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit query_dataapi? +

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

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

query_dataapi is provided by the Cloudera Data Visualization MCP Server MCP server (kevintalbert/cdv-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.