High Risk →

lake_query

lake_query

How to control lake_query ↓

What lake_query does on Amazon Location Service MCP Server

AI agents invoke lake_query to trigger actions in Amazon Location Service 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.

High Risk

Why lake_query needs a policy

The name 'lake_query' suggests querying a data lake (e.g., AWS Lake Formation or similar). 'Query' operations can range from simple reads to executing arbitrary SQL that may include destructive statements. Given the empty description, confidence is low. The most likely interpretation is Execute (running a query against a data lake), but without more context it could be Read.

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

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

How to control lake_query

PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon Location Service 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.

  1. Create a free account and register Amazon Location Service MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
RATE-LIMIT THIS TOOL →

Free to start. No card required.

Related tools and policies

Go deeper

Questions about lake_query

What does the lake_query tool do? +

lake_query. It is categorised as a Execute tool in the Amazon Location Service 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 Location Service 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 Location Service 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 Location Service MCP Server MCP server (awslabs.aws-location-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 Location Service MCP Server tool call.

Start from Amazon Location Service 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.

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

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.