deploy_tokens_revoke

Run deploy-tokens.revoke through the Appaloft application operation catalog. Shared with CLI and HTTP/API.

SERVERAppaloft SOURCE@appaloft/mcp

High RISK CLASS

Category Execute

Parameters 53 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/appaloft-mcp/deploy-tokens-revoke.md

WHAT IT DOES

What deploy_tokens_revoke does on Appaloft

AI agents invoke deploy_tokens_revoke 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
`reason`	string	—
`tokenId`	string	Yes
`confirmation`	object	Yes
`idempotencyKey`	string	—
`organizationId`	string	Yes

Parameters from the server's own tool schema.

RISK

Why deploy_tokens_revoke is rated High

deploy_tokens_revoke 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

RECOMMENDED RULE

The rule that runs deploy_tokens_revoke 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 deploy_tokens_revoke, this is the rule to start with:

deploy_tokens_revoke Rate-limited

deploy_tokens_revoke 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "deploy_tokens_revoke": {
      "limits": [
        {
          "counter": "deploy_tokens_revoke_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Appaloft, apply this rule, and every deploy_tokens_revoke call is checked against it from then on.

FAQ

Questions about deploy_tokens_revoke

What does the deploy_tokens_revoke tool do? +

Run deploy-tokens.revoke 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.

What parameters does deploy_tokens_revoke accept? +

deploy_tokens_revoke accepts 5 parameters: reason, tokenId, confirmation, idempotencyKey, organizationId. Required: tokenId, confirmation, organizationId. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on deploy_tokens_revoke? +

Register the Appaloft MCP server in PolicyLayer and add a rule for deploy_tokens_revoke: 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.

What risk level is deploy_tokens_revoke? +

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

Can I rate-limit deploy_tokens_revoke? +

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

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

deploy_tokens_revoke 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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