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sam_deploy

sam_deploy

How to control sam_deploy ↓

What sam_deploy does on Amazon Data Processing MCP Server

AI agents invoke sam_deploy 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.

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Why sam_deploy needs a policy

SAM deploy is a command that provisions and updates cloud infrastructure, executing code and triggering complex external operations (creating Lambda functions, API gateways, databases, etc.). The effects depend on the SAM template provided as arguments.

From the tool's definition Tool name 'sam_deploy' refers to AWS SAM (Serverless Application Model) deployment, which executes infrastructure-as-code operations that trigger external AWS services.

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

How to control sam_deploy

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 sam_deploy:

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

sam_deploy 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 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 sam_deploy

What does the sam_deploy tool do? +

sam_deploy. 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 sam_deploy? +

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

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

Can I rate-limit sam_deploy? +

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

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

sam_deploy 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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