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fal.ai MCP Server

fal.ai MCP Server

by thenavidm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Request queue cancellation

cancel_job
Destructive

Cancel a fal.ai job by model ID and request ID once confirmed. A cancellation receipt does not guarantee processing stopped or credits refunded.

Instructions

Confirmed native cancellation request. Cancellation receipt is not proof processing stopped or credits were refunded; current provider state controls eligibility. No retry.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model_id": "<model_id>",
      "request_id": "<request_id>"
    },
    "name": "cancel_job"
  }
}

Input Schema

NameRequiredDescriptionDefault
accountNoExact configured isolated API-key profile label.
confirmNoSet true only when the user asked for exactly this action.
model_idYesExact current catalog endpoint ID. Never guess model names or parameter mappings.
request_idYesExact queue receipt ID; status/result/cancel use its owner/app root, without inference subpaths.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.0.1
    • changedInput schema / properties / confirm / description
      Previous value: -"Explicit approval for the requested paid work, mutation, upload or private file."New value: +"Set true only when the user asked for exactly this action."
  2. First observedv2.0.0

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare destructiveHint=true, idempotentHint=false and readOnlyHint=false, so the safety profile is covered. The description still adds real value beyond them: a cancellation receipt is not proof that processing stopped or credits were refunded, eligibility is governed by current provider state, and retrying is discouraged. That is substantive behavioral context, though it omits permission/auth prerequisites.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short, front-loaded sentences with no filler; the core action is stated first and the caveats follow. Sentence-fragment style is terse and readable, though the clipped phrasing slightly hurts clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive mutation with no output schema, the description covers the critical caveats (receipt is not proof, provider state controls eligibility, no retry) and 100% of parameters are schema-documented. What is missing is the expected return shape beyond the receipt and any auth/permission requirements.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents account, confirm, model_id and request_id in detail. The description only weakly gestures at the confirm parameter with the word 'Confirmed' and adds no syntax or format meaning beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action (cancellation of a queued request/job) and the tool name plus title make the resource clear. It does not, however, distinguish itself from nearby siblings like delete_request_payloads or get_job_status, so an agent must rely on the name alone to route correctly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use / when-not-to-use guidance and no named alternative among the many job-related siblings. The only directive offered is the terse 'No retry,' which is a constraint rather than a usage rule.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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