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ExecuteRangeQuery

ExecuteRangeQuery

How to control ExecuteRangeQuery ↓

What ExecuteRangeQuery does on AWS Documentation MCP Server

AI agents invoke ExecuteRangeQuery to trigger actions in AWS Documentation 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 ExecuteRangeQuery needs a policy

The tool name contains 'Execute', which indicates it runs code or triggers operations. Query execution can have side effects depending on the underlying service and arguments provided. Without documentation details, a conservative assessment treats this as Execute rather than Read, as query execution against AWS systems could potentially modify state or trigger costly operations.

From the tool's definition Tool name 'ExecuteRangeQuery' indicates execution of a query operation. The empty description prevents full certainty of what data source and operations are permitted, but the verb 'Execute' combined with 'Query' on an AWS Documentation server suggests…

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

How to control ExecuteRangeQuery

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "ExecuteRangeQuery": {
      "limits": [
        {
          "counter": "executerangequery_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

ExecuteRangeQuery 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 AWS Documentation 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 →

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Related tools and policies

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Questions about ExecuteRangeQuery

What does the ExecuteRangeQuery tool do? +

ExecuteRangeQuery. It is categorised as a Execute tool in the AWS Documentation 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 ExecuteRangeQuery? +

Register the AWS Documentation MCP Server MCP server in PolicyLayer and add a rule for ExecuteRangeQuery: 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 AWS Documentation MCP Server. Nothing to install.

What risk level is ExecuteRangeQuery? +

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

Can I rate-limit ExecuteRangeQuery? +

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

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

ExecuteRangeQuery is provided by the AWS Documentation MCP Server MCP server (awslabs.aws-documentation-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 AWS Documentation MCP Server tool call.

Start from AWS Documentation 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 AWS Documentation MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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