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Documentation Index

Fetch the complete documentation index at: https://docs.artificialstudio.ai/llms.txt

Use this file to discover all available pages before exploring further.

Once the MCP server is connected, just talk to your AI normally. Here are example prompts that hit different tools — use them as inspiration.

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Generate an image

“Generate a photo of a golden retriever puppy in a field of sunflowers using Flux Schnell.”
Your AI will:
  1. Call get_tool_detail with tool_slug: "create-image" to see model options.
  2. Call generate with tool: "create-image", input: { model: "flux-schnell", prompt: "..." }.
  3. Poll check_generation until done.
  4. Show you the image URL.

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Let the AI pick the model

“Make me an image of a cyberpunk city. Use whichever model is cheapest.”
The AI will call get_tool_detail, compare cost across models, and pick the cheapest before calling generate.

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Generate a video from an image

“Animate this image with a gentle breeze and the subject smiling. Make it 4 seconds.” [attaches image]
The AI will:
  1. Find animate-image via search_tools.
  2. Upload or reference the image (client-dependent).
  3. Call generate with tool: "animate-image", input: { model: "veo3-1-lite-image-to-video", image_url: "...", prompt: "...", duration: 4 }.
  4. Poll every ~10 seconds — videos take 60–180 seconds.
For videos, remind the AI the job is async so it doesn’t ask every second. Claude Code and Cursor handle this automatically via poll_after_seconds.

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Text to speech

“Read this paragraph aloud in a British female voice. Use ElevenLabs.”
AI calls text-to-speech tool with the chosen model. Audio is a short job (~10s) — polling finishes quickly.

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Check your credits before generating

“How many credits do I have? Then generate 4 variations of ‘neon lights at night’ with Nano Banana.”
AI calls get_account first, tells you the balance, then runs generate four times. Bonus: it will warn you if the total cost exceeds your balance.

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List recent work

“What have I generated in the last hour?”
AI calls list_generations with limit: 20 and shows you the results, filtering by time in its response.

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Chain generations

“Generate an image of a dragon, then animate it into a 4-second video.”
AI runs two generate + check_generation cycles, feeding the image URL from the first into the second.

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Prompts that won’t work well

  • “Just generate it, don’t wait” — The async pattern doesn’t have a “fire and forget” mode for MCP. Your AI will still poll.
  • “Make 100 images in parallel” — MCP clients typically serialize tool calls. Use the REST API for bulk jobs.
  • “Edit my Photoshop file” — MCP tools return URLs; they don’t touch local files unless your AI client has file-write capability.

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Tips for better results

  1. Name the model when you care: “Use Nano Banana Pro” avoids a get_tool_detail round-trip and ambiguity.
  2. Be specific about cost limits: “Keep it under 50 credits” lets the AI filter models.
  3. Tell it to wait: “This might take 2 minutes, be patient” — helps with clients that otherwise time out waiting for a tool response. (The server no longer times out; but some clients have their own UX timers.)

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Next steps

Tool reference

Full details on every tool.

Browse models

See all models available via MCP too.