Low Risk

get_schedule_details

get_schedule_details

How to control get_schedule_details ↓

What get_schedule_details does on Amazon Redshift MCP Server

AI agents call get_schedule_details to retrieve information from Amazon Redshift MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

Why get_schedule_details needs a policy

The 'get_' prefix strongly indicates a read-only operation that retrieves schedule information without modification. No destructive, write, financial, or execute operations are suggested by the name. Empty description reduces confidence slightly, but naming convention is reliable. Severity is low because reading schedule details has minimal blast radius even if misused by an AI agent.

From the tool's definition Tool name 'get_schedule_details' follows the GET/read pattern (get_*). Description is empty, limiting certainty. The sibling tools and server context (Amazon Redshift) suggest data retrieval operations.

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

How to control get_schedule_details

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_schedule_details": {}
  }
}

get_schedule_details is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Amazon Redshift 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.
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Related tools and policies

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Questions about get_schedule_details

What does the get_schedule_details tool do? +

get_schedule_details. It is categorised as a Read tool in the Amazon Redshift MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_schedule_details? +

Register the Amazon Redshift MCP Server MCP server in PolicyLayer and add a rule for get_schedule_details: 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 Redshift MCP Server. Nothing to install.

What risk level is get_schedule_details? +

get_schedule_details is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_schedule_details? +

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

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

get_schedule_details is provided by the Amazon Redshift MCP Server MCP server (awslabs.redshift-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 Redshift MCP Server tool call.

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

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

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