deployments_prune
Run deployments.prune through the Appaloft application operation catalog. Shared with CLI and HTTP/API.
This record as markdown: /tools/appaloft-mcp/deployments-prune.md
What deployments_prune does on Appaloft
AI agents invoke deployments_prune to trigger actions in Appaloft. 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 |
|---|---|---|---|
before | string | Yes | |
dryRun | boolean | — | |
serverId | string | — | |
resourceId | string | — | |
deploymentId | string | — |
Parameters from the server's own tool schema.
Why deployments_prune is rated High
deployments_prune triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs deployments_prune safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Appaloft, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For deployments_prune, this is the rule to start with:
deployments_prune 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 Appaloft, apply this rule, and every deployments_prune call is checked against it from then on.
Questions about deployments_prune
Run deployments.prune through the Appaloft application operation catalog. Shared with CLI and HTTP/API. It is categorised as a Execute tool in the Appaloft MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
deployments_prune accepts 5 parameters: before, dryRun, serverId, resourceId, deploymentId. Required: before. The full parameter table on this page comes from the server's own tool schema.
Register the Appaloft MCP server in PolicyLayer and add a rule for deployments_prune: 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 Appaloft. Nothing to install.
deployments_prune 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 deployments_prune 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 deployments_prune. 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.
deployments_prune is provided by the Appaloft MCP server (@appaloft/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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