This record as markdown: /tools/io-github-kivanccakmak-yaver/cloud-cli.md
What cloud_cli does on Yaver
AI agents invoke cloud_cli to trigger actions in Yaver. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
args | array | Yes | CLI arguments (e.g. ['s3', 'ls']) |
provider | string | Yes | aws, gcloud, or az |
Parameters from the server's own tool schema.
Why cloud_cli is rated High
This tool executes external commands against major cloud providers (AWS, GCP, Azure) without apparent restrictions or argument validation. An AI agent with this capability could execute destructive operations (delete databases, drop storage, terminate instances), deploy malicious code, exfiltrate data, modify security policies, or incur massive financial charges.
From the tool's definition Tool description states 'Run AWS, GCP, or Azure CLI commands' — explicitly permits execution of arbitrary cloud provider CLI commands with full access to cloud infrastructure.
Attacks that exploit this kind of access
The rule that runs cloud_cli safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For cloud_cli, this is the rule to start with:
cloud_cli 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Yaver, apply this rule, and every cloud_cli call is checked against it from then on.
Questions about cloud_cli
Run AWS, GCP, or Azure CLI commands. It is categorised as a Execute tool in the Yaver MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
cloud_cli accepts 2 parameters: args, provider. Required: args, provider. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for cloud_cli: 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 Yaver. Nothing to install.
cloud_cli 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 cloud_cli 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 cloud_cli. 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.
cloud_cli is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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