Medium Risk

create_datasource

create_datasource

How to control create_datasource ↓

What create_datasource does on Amazon Data Processing MCP Server

AI agents use create_datasource to create or update resources in Amazon Data Processing MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Amazon Data Processing MCP Server environment.

Medium Risk

Why create_datasource needs a policy

The 'create_datasource' name strongly suggests creating or provisioning a new data source, which is a reversible Write operation. Without description details, confidence is moderate. The severity is medium because creating datasources in AWS could have cost implications and affect system architecture, but is not inherently destructive or financial.

From the tool's definition Tool name 'create_datasource' indicates creation of a new data resource. Description is empty, limiting definitive assessment. Context suggests AWS data processing operations.

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

How to control create_datasource

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 create_datasource:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_datasource": {
      "limits": [
        {
          "counter": "create_datasource_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

create_datasource stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Amazon Data Processing 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 create_datasource

What does the create_datasource tool do? +

create_datasource. It is categorised as a Write tool in the Amazon Data Processing MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_datasource? +

Register the Amazon Data Processing MCP Server MCP server in PolicyLayer and add a rule for create_datasource: 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 create_datasource? +

create_datasource is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_datasource? +

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

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

create_datasource 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.

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.

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