AI agents invoke sam_deploy to trigger actions in Prometheus 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.
SAM deployments execute infrastructure-as-code operations that create or modify AWS resources (Lambda functions, API Gateways, databases, IAM roles, etc.). While the description is empty, the tool name combined with the Prometheus/AWS context and similar infrastructure tools on the server strongly indicate this performs Execute-category operations.
From the tool's definition Tool name 'sam_deploy' indicates deployment of AWS Serverless Application Model (SAM) applications. The sibling tools on this server include infrastructure and policy modification tools (add_inline_policy, add_user_to_group), suggesting this server manages…
Documented attack patterns abuse exactly the kind of access sam_deploy gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Prometheus MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for sam_deploy:
{
"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.
Free to start. No card required.
sam_deploy. It is categorised as a Execute tool in the Prometheus MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Prometheus 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 Prometheus MCP Server. Nothing to install.
sam_deploy is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
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.
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.
sam_deploy is provided by the Prometheus MCP Server MCP server (awslabs.prometheus-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Prometheus 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 Prometheus MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.