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Shotstack MCP Server

by thenavidm
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TypeScript
Hybrid

Generate Asset

generate_asset
Destructive

Create a single image, video, or audio asset from a text prompt without rendering a full edit. Cached identical prompts are reused; explicit confirmation is required.

Instructions

Generate a single image, video or audio asset from a text prompt without rendering a full edit. Submit a prompt-bearing asset; the response is immediate when an identical asset has been generated before (results are cached by prompt, model and options), otherwise the job is queued and can be polled via the status endpoint.

Generation is billed in credits per asset. Identical repeat requests resolve from the cache at no charge.

Base URL: https://api.shotstack.io/edit/{version} Explicit confirmation is required for this exact action; provider charges, hosting, sharing or deletion may apply. Never automatically resubmit unknown outcomes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetNo
lengthNoThe length, in seconds, of the clip the asset fills. A model that generates to a duration takes it from this value in place of its own duration option. Other models ignore it.
accountNoNamed private Shotstack account; selects private credentials and stage/v1 environment.
confirmNoMust be true for this exact requested render, generation, mutation, upload URL or deletion.
payloadNoComplete JSON request body instead of body flags. Preserves current endpoint fields and values.
payload_fileNoRegular local JSON body file, at most 5 MB. Cannot be mixed with body flags or payload.
idempotency_keyNoA key that makes this request its own generation. Retrying with the same key returns the job it first created instead of generating and billing again, and a new key generates afresh even when the asset matches an earlier one. Without a key, identical assets share one cached result. For 24 hours a key reused for a different asset is rejected; after that it returns its first result.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.8/5.0
Behavior4/5

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

The description adds significant behavioral context beyond the annotations: caching by prompt/model/options, credit billing, immediate vs queued responses, polling via status endpoint, and the need for explicit confirmation. These go well beyond the high-level annotations and are crucial for correct agent behavior, especially around repeat submissions and billing.

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

Conciseness3/5

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

The description is somewhat verbose, with a long first sentence and separate paragraphs for caching, billing, base URL, and confirmation. While the information is relevant, it could be more front-loaded and tightly structured; the base URL and confirmation warning feel appended rather than integrated.

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?

Given 7 parameters, nested objects, no output schema, and high schema coverage, the description covers the essential behavioral context: async queueing, polling, credits, caching, and explicit confirmation. It does not explain the idempotency_key interaction with caching despite the schema doing so, which is a minor gap for a destructive action.

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 86%, so the schema already documents most parameters in detail. The description adds limited parameter-specific information beyond the schema, mostly reinforcing the prompt concept. The mention of caching by prompt, model and options indirectly relates to parameters but does not add syntax or constraints beyond what the schema provides.

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?

Description states a clear verb and resource: 'Generate a single image, video or audio asset from a text prompt.' It also distinguishes from 'rendering a full edit' and names the polling endpoint for queued jobs. The sibling list includes 'render' and 'render_template', so this distinction is useful, though the description could more explicitly tell the agent when to use generate_asset vs render.

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

Usage Guidelines4/5

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

The description contrasts generation with full renders ('without rendering a full edit') and explains the caching behavior that affects repeat calls. However, it does not explicitly state when to prefer this tool over siblings like 'render' or 'render_template', leaving some selection ambiguity.

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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