lake_query · Amazon Data Processing MCP Server MCP

WHAT IT DOES

What lake_query does on Amazon Data Processing MCP Server

AI agents invoke lake_query to trigger actions in Amazon Data Processing 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.

THE RISK

High Risk

Why lake_query needs a policy

The name 'lake_query' strongly suggests interaction with a data lake (e.g., AWS Lake Formation or S3 data lake via Athena/Glue). 'Query' could range from a read operation to executing arbitrary SQL that may include destructive statements. Given the empty description, confidence is reduced.

From the tool's definition Tool name 'lake_query' on a data processing server; description is empty and uninformative.

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

POLICY

How to control lake_query

PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon Data Processing MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for lake_query:

policy.json

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

lake_query 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.

Create a free account and register Amazon Data Processing MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RATE-LIMIT THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Amazon Data Processing MCP Server tools

Destructive bulk_delete_by_criteria bulk_delete_by_criteria Destructive cache_delete Delete a value from the cache. Destructive cache_delete_many Delete multiple values from the cache. Destructive cache_delete_multi Delete multiple values from the cache (alias for delete_many). Destructive cancel_logs_insight_query cancel_logs_insight_query Destructive CancelAHORunBatch CancelAHORunBatch Destructive delete delete Destructive delete_access_key delete_access_key

All 805 Amazon Data Processing MCP Server tools →

Execute tools on other servers

Android Forensics ADB MCP Server adb_shell_command EMBA-MCP run_emba_scan Frida Game Hacking MCP remove_breakpoint Procmon request_elevation

Go deeper

Govern code and CI agents → Branch allowlists, approval on merges, and rate caps on the build and pipeline tools agents trigger.
High-risk tools in Amazon Data Processing MCP Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about lake_query

What does the lake_query tool do? +

lake_query. It is categorised as a Execute tool in the Amazon Data Processing 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 lake_query? +

Register the Amazon Data Processing MCP Server MCP server in PolicyLayer and add a rule for lake_query: 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 Amazon Data Processing MCP Server. Nothing to install.

What risk level is lake_query? +

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

Can I rate-limit lake_query? +

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

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

lake_query is provided by the Amazon Data Processing MCP Server MCP server (awslabs.aws-dataprocessing-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Amazon Data Processing MCP Server tool call.

Start from Amazon Data Processing MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →

Free to start. No card required.

805 Amazon Data Processing MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.