clerk.get_machine
Retrieve a machine by id from a connected Clerk instance. Call clerk.get_connected_accounts first. Pass clerk_instance_id to target a specific connection, or omit it to use the default account. Returns machine metadata including scoped_machines. Cost = 3 tokens.
This record as markdown: /tools/io-github-vee3io-vee3/clerk.get-machine.md
What clerk.get_machine does on Vee3
AI agents call clerk.get_machine to retrieve information from Vee3 without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
machine_id | string | Yes | Clerk machine id (mch_...) to retrieve or modify. |
clerk_instance_id | object | — | Clerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account. |
Parameters from the server's own tool schema.
Why clerk.get_machine is rated Low
Tool queries and returns machine metadata without modifying, deleting, or executing operations.
From the tool's definition Retrieve a machine by id from a connected Clerk instance.
Attacks that exploit this kind of access
The rule that runs clerk.get_machine safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Vee3, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For clerk.get_machine, this is the rule to start with:
clerk.get_machine is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Vee3, apply this rule, and every clerk.get_machine call is checked against it from then on.
Questions about clerk.get_machine
Retrieve a machine by id from a connected Clerk instance. Call clerk.get_connected_accounts first. Pass clerk_instance_id to target a specific connection, or omit it to use the default account. Returns machine metadata including scoped_machines. Cost = 3 tokens. It is categorised as a Read tool in the Vee3 MCP Server, which means it retrieves data without modifying state.
clerk.get_machine accepts 2 parameters: machine_id, clerk_instance_id. Required: machine_id. The full parameter table on this page comes from the server's own tool schema.
Register the Vee3 MCP server in PolicyLayer and add a rule for clerk.get_machine: 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 Vee3. Nothing to install.
clerk.get_machine is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the clerk.get_machine 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 clerk.get_machine. 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.
clerk.get_machine is provided by the Vee3 MCP server (https://mcp.vee3.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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