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The MCP server exposes 6 tools. AI clients discover them automatically via tools/list — you don’t call them directly; your AI does.

search_tools

Find the right Artificial Studio tool for a task. Arguments Returns: { data: Tool[] } with matching tools, each including input schemas and pricing. Example prompt
“What tools does Artificial Studio have for making music?”

get_tool_detail

Get full details for one tool: all models, input schemas, pricing. Arguments Returns: the tool object with models[], each with slug, name, cost, costUnit, and inputSchema. Call this before generate if you want your AI to pick the best/cheapest model, or to show the user options.

generate

Submit a generation job. Returns immediately with a job_id — the job runs asynchronously in the background.
This tool is async. After calling, poll check_generation with the returned job_id every few seconds until status is "success" or "error". Videos and audio can take minutes.
Arguments Example call
Response
Typical ETA hints poll_after_seconds is always clamped between 3s and 10s.

check_generation

Poll a generation by its job_id. Call this until done: true. Arguments Response — still running
Response — success
Response — error
output and thumbnail are only present on success. error is only present on failure. When done: true, stop polling.

list_generations

List recent generations from your account. Arguments Useful for “show me my last video” style prompts.

get_account

Returns credits, plan, and basic account info for the authenticated user. Arguments: none. Returns
Your AI can use this to warn you before running expensive jobs.

Error handling

Tool calls that fail throw standard MCP errors. Common causes: Your AI will typically retry or ask you for clarification — behavior depends on the client.

Next steps

Async & polling

Deep dive on the async generation pattern.

Examples

Example prompts and conversations.