replicate_cancel_prediction
Cancel a running Replicate prediction.
This record as markdown: /tools/io-github-malamutemayhem-unclick-mcp-server/replicate-cancel-prediction.md
What replicate_cancel_prediction does on UnClick
AI agents invoke replicate_cancel_prediction to trigger actions in UnClick. 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 |
|---|---|---|---|
api_token | string | Yes | |
prediction_id | string | Yes |
Parameters from the server's own tool schema.
Why replicate_cancel_prediction is rated High
Cancelling a running prediction is an action that triggers an external operation (stopping an in-progress computation on Replicate's platform). It is not purely destructive (no data is deleted) nor a simple read/write — it actively intervenes in an ongoing external process. The blast radius is medium: a misuse could abort legitimate running jobs, wasting compute and potentially disrupting workflows.
From the tool's definition Cancel a running Replicate prediction
Attacks that exploit this kind of access
The rule that runs replicate_cancel_prediction safely
PolicyLayer is an MCP gateway: it sits between your AI agents and UnClick, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For replicate_cancel_prediction, this is the rule to start with:
replicate_cancel_prediction 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 UnClick, apply this rule, and every replicate_cancel_prediction call is checked against it from then on.
Questions about replicate_cancel_prediction
Cancel a running Replicate prediction. It is categorised as a Execute tool in the UnClick MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
replicate_cancel_prediction accepts 2 parameters: api_token, prediction_id. Required: api_token, prediction_id. The full parameter table on this page comes from the server's own tool schema.
Register the UnClick MCP server in PolicyLayer and add a rule for replicate_cancel_prediction: 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 UnClick. Nothing to install.
replicate_cancel_prediction 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 replicate_cancel_prediction 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 replicate_cancel_prediction. 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.
replicate_cancel_prediction is provided by the UnClick MCP server (@unclick/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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