"Tools and Methods for Image Generation" matching MCP tools:

• create_generation_request

  Cannon Studio

  Create billable async Cannon Studio generation work only after explicit user approval. Requires OAuth or a developer API key; can spend credits up to max_credits and cannot be cancelled through MCP after submission. Use estimate_generation_cost first, then set confirmed=true and a user-approved max_credits cap. This tool does not create API keys, charge payment methods directly, or delete assets.

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• generate_image

  Avocado AI

  Generate an AI image using Avocado AI. Returns a jobId immediately; image generation completes in 10-60 seconds. After calling, use the check_job tool with the returned jobId to retrieve the result, once complete, check_job returns the image inline so it renders directly in chat. Run models_list to see available models. Costs 1-4 credits per image depending on model and quality.

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• use

  Vaaya

  Execute a single call that `consult` handed you, and bill on success. Used for any external capability (image/video/audio generation, web search, scraping, email, document parsing, code sandbox, browser automation, embeddings, etc.). The server validates params against a registered schema and proxies to the upstream — you never pass URLs or API keys. Always get the exact (service, action, params, max_cost_cents) from `consult` first — don't guess them.

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• picsart_enhance

  Picsart GenAI

  Upscales and enhances an image — sharpens edges, denoises, and raises resolution by an optional scale factor. Auto-picks the newest enabled Picsart upscale / enhance model unless overridden via the `model` param. Use this when the user asks to "upscale", "enhance", "make it higher resolution", "sharpen", "clean up this photo", or "make this 4k". Do NOT use this to remove the background (use `picsart_remove_bg`), replace the background (use `picsart_change_bg`), convert raster to SVG (use `picsart_vectorize`), or generate a new image (use `picsart_generate`). Required input: `image` — a publicly-accessible URL, not a local file path. Optional: `model` to pin a specific enhance model, `scaleFactor` (e.g. 2 or 4) for upscale ratio. Example: `{ image: "https://example.com/photo.jpg", scaleFactor: 4 }`. Returns `{ assets, id, model, created_at, summary, why_relevant, url, results: [{ url, metadata? }], drive? }` plus a `resource_link` block per result URL. `id` is the SDK's generation handle; `metadata` may include model-specific tags. Spends credits. Requires Authorization: Bearer <picsart_token>.

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• get_job_result

  Sats4AI - Bitcoin-Powered AI Tools

  Retrieve the final output of a completed async job. Call ONLY after check_job_status returns status='completed' — calling on a non-completed job returns an error. Returns JSON whose shape depends on jobType: video/video-image → { videoUrl, duration }; image-3d → { modelUrl } (GLB format); transcription → { text, language, segments }; epub-audiobook → { audioUrl, chapters }; ai-call → { transcript, duration, summary }. All URLs are temporary (valid ~1 hour) — download immediately. This tool is free and does not require payment. Do NOT use for synchronous tools — those return results directly.

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• generate_image

  Goodeye

  Generate one or more images from a text prompt, billed to the caller's credits. Requires authentication. Anonymous image generation is available only via the REST API (``POST /v1/image-generators/{id}/runs``); the MCP transport always authenticates. Resolution order for the generator (highest priority first): 1. A deployed ``generator`` ref (``uuid@version`` or bare UUID): pins the deployed version config. 2. The ``model`` control path (authenticated one-off, ephemeral). Not usable from published templates. 3. A tier ``generator`` ref (``system:<tier>``): resolves to the tier's current best model (auto-upgrade). Available tiers: ``system:image-standard`` (default), ``system:image-premium``, ``system:image-edit`` (image-to-image, requires ``reference_image_url``). 4. Default: ``system:image-standard`` when no generator or model is given. ``generator`` and ``model`` are mutually exclusive. For ``image_to_image`` generators, ``reference_image_url`` is required and must be a public HTTP or HTTPS URL. For ``text_to_image`` generators, providing ``reference_image_url`` is rejected. Billing: spend is deducted from the caller's monthly credit balance. ``BudgetExhausted`` (402) and ``AccountSuspended`` (403) propagate if the balance is zero or the account is suspended. ``visibility`` sets the access level of the hosted copy of each image: ``public`` (default) returns a link that opens in any browser; ``private`` returns a link only you can open and forward to people you choose, while the plain URL stays locked. Returns: ``{run_id, model_tier_or_model, image_url, image_urls, width, height, num_images, cost_usd, duration_ms, status, created_at, error_code, error_message, hosted_images}``. ``hosted_images`` carries the durable Goodeye-hosted copy of each image with its ``url`` (the browser-viewable link) and ``visibility``. The prompt is never stored; only its hash is persisted on the run row.

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• aetherwave_generate_image

  AetherWave Studio

  Generates one or more images from a text prompt (T2I) or a text prompt + reference image(s) (I2I). Submits the job, polls until terminal, and returns the final image URLs. Default model is 'grok-imagine-t2i' (fast, 6 images per generation, 5 credits). Use list_image_models to see the full lineup with pricing. For I2I, pass `referenceImages` as an array of public image URLs and pick a model with I2I support (e.g. 'grok-imagine-i2i', 'wan-2.5-spicy-i2i'). ## Model selection guide (when the user does not specify a model) Default: `grok-imagine-t2i` (5 cr, 6 outputs per call, fast, general purpose). **Strong recommendation: when a single high-quality output is what's wanted** (most agent / one-shot workflows), prefer `gpt-image-2-t2i` (9 cr @ 1K / higher @ 2K, single deterministic image, best general quality across realism, illustration, typography, and composition; supports up to 2K resolution and most aspect ratios including auto). This is the front-runner for serious creative output where you don't need to pick from 6 variations. Pick a different model when the prompt has these signals: - "single best result" / "one image" / production / no time to pick from variations -> `gpt-image-2-t2i` (9 cr, 1 output, top general quality) - "photoreal" / "photo of" / "realistic" -> `gpt-image-2-t2i` (9 cr, best general realism) or `imagen-4` (12 cr, very high quality) or `z-image-turbo` (3 cr, fastest) - "highest quality" / "premium" / no budget -> `gpt-image-2-t2i` at 2K, or `grok-imagine-quality-t2i` (16 cr @ 1K, 22 cr @ 2K), or `imagen-4-ultra` - Text inside the image (signs, posters, typography) -> `ideogram-v3-t2i` (best in class) or `gpt-image-2-t2i` (also strong) - Artistic / painterly / stylized -> `midjourney-t2i` - Album art / cover art -> `gpt-image-2-t2i` for one strong image; `grok-imagine-t2i` for 6 variations to choose from; `seedream-v4-t2i` if 4K wanted - Logo or design with embedded text -> `ideogram-v3-t2i` - NSFW / adult / explicit -> `wan-2.5-spicy-t2i` (auto-tags creation as 18+; routes to adult gallery) - Cheapest possible / quick test -> `z-image-turbo` (3 cr) - Multiple variations to compare -> keep `grok-imagine-t2i` (6 outputs default) or use `numImages` on a multi-output model For I2I (reference image provided): prefer the dedicated `aetherwave_edit_image` tool for "change something in this image" intent. Use `aetherwave_generate_image` with I2I models only when you specifically want style transfer (`midjourney-i2i`), premium quality (`grok-imagine-quality-i2i`), or adult content (`wan-2.5-spicy-i2i`). Always pass an explicit `aspectRatio` (e.g. "1:1" for square album art, "16:9" for video thumbnails, "9:16" for shorts/reels). Some upstream providers reject submissions with no aspect ratio. Ask the user only when: - The prompt contradicts itself (e.g., "highest quality but cheapest") - The user requested "the best model" with no context, surface 2-3 options with tradeoffs - A single generation would cost more than 20 credits and the user has not confirmed

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• generate_image

  BananaBanana Image & Video Generation

  Start an AI image generation (Google Nano Banana family). Charges the account balance immediately and returns a job_id — poll get_result for the finished image URLs. Typical completion: 10–60 seconds. Costs $0.03–$0.20 per image depending on model and resolution (see list_models). Failed generations are automatically refunded. Generating several images at once (number_of_images > 1) is a batch: the first call returns a price quote and charges nothing — repeat the call with confirm_cost set to the quoted amount to start. Example: {"prompt": "studio photo of a ceramic mug on linen, soft daylight", "model": "nano-banana-2", "aspect_ratio": "4:5", "resolution": "1024"}

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• prepare_image_upload

  Avocado AI

  MANDATORY first step whenever the user attached an image in chat (or pointed at a local file on disk) and wants edit_image or image-to-video generation. Returns a signed PUT URL plus a file_id. How the bytes get uploaded depends on WHERE you run, and the discriminator is network access to the URL, not shell access: (a) Claude.ai (web, desktop, or mobile app): this tool renders an inline upload widget. The user drops the image into it; it uploads from their browser and pushes the file_id back automatically. Your code-execution sandbox has NO network route to the signed URL — a chat attachment sitting on the sandbox filesystem does NOT mean you can upload it. NEVER attempt curl/fetch/Python uploads from a sandbox and never investigate domain allowlists; just ask the user (one short sentence) to drop the image into the widget, then stop and wait. (b) Claude Code / a CLI with a real shell on the user's machine: run the ready-made curl PUT from the response text. Then call edit_image or generate_video with file_id=<returned id>. edit_image and generate_video do NOT accept base64 — calling them with raw image bytes WILL fail. This tool is the only working path for chat attachments. Set `purpose` to 'edit' or 'video' so the upload widget points the user at the right downstream tool.

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• agent_verify

  Colour Memory

  Verify that an AI-generated image actually used the colours specified in an agent_brief call. Supply the generated image (URL or base64) and the target palette from agent_brief colour_tokens. Returns a fidelity score 0-100, dE2000 distance per colour, match quality per colour (accurate/acceptable/drifted/ignored), and an overall verdict. Use after agent_brief + image generation to close the colour loop.

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• deploy_image_generator

  Goodeye

  Deploy a reusable image generator that workflows reference to produce images from a chosen model: creates it or appends a version. An image generator is a named, versioned configuration that routes image generation calls to a specific model. Generators are private and owner-scoped. Workflows reference them by UUID or ``uuid@version``. You cannot deploy a new generator whose ``name`` matches an active platform ``scope=system`` generator (those are tier-level configs that are run-only and not listed or fetched). Versioning: the first deploy with a given ``name`` creates the generator at version 1. Re-deploying the same ``name`` appends a new version and requires ``expected_version_token`` from the latest known version (returned by deploy/list/get). A new generator must omit the token; an existing one without a token returns Conflict. Deploy-time validation: the ``model`` is checked against the pricing layer. A model that does not resolve to a known image endpoint with an authoritative price is rejected before any row is written. Returns: ``{generator_id, name, description, current_version, version, version_token, status, scope, provider, model, generation_contract, config_hash, created_at}``. Persist ``version_token`` for the next re-deploy.

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• update_image

  Goodeye

  Update visibility, TTL, or the private view link of a hosted image. Caller must own it. ``visibility`` flips the access level: ``"public"`` or ``"private"``. Omit to leave unchanged. ``ttl_seconds`` and ``permanent`` are mutually exclusive. ``permanent`` clears the expiry so the image lives indefinitely. ``ttl_seconds`` sets a new expiry relative to now (positive integer). Omitting both leaves the current expiry unchanged. ``rotate_view_secret`` issues a fresh private view link and invalidates every link shared earlier for this image, so use it to un-share a private image. For a private image the returned ``url`` is the current view link. Returns the updated image record. Raises ``image_not_found`` (404) when the image is absent, expired, or owned by another user.

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• picsart_change_bg

  Picsart GenAI

  Replaces the background of an image with a new scene described by a prompt, keeping the foreground subject intact. Auto-picks the newest enabled Picsart change-bg model unless overridden via the `model` param — no need to call `picsart_list_models` first. Use this when the user wants to "change the background to X", "put this on a beach", "swap the background for a marble counter", or any compositing where the subject is kept and the backdrop changes. Do NOT use this to strip the background to transparency (use `picsart_remove_bg`), upscale or sharpen (use `picsart_enhance`), convert raster to SVG (use `picsart_vectorize`), or generate a brand-new image from scratch (use `picsart_generate`). Required inputs: `image` — a publicly-accessible URL, not a local file path — and `prompt` describing the new background. Optional: `model` to pin a specific change-bg model. Example: `{ image: "https://example.com/product.jpg", prompt: "polished marble countertop with soft window light" }`. Returns `{ assets, id, model, created_at, prompt, summary, why_relevant, url, results: [{ url, metadata? }], drive? }` plus a `resource_link` block per result URL. `id` is the SDK's generation handle; `metadata` may include model-specific tags (e.g. `exploreImageId` for Recraft Explore models). Spends credits. Requires Authorization: Bearer <picsart_token>.

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• picsart_vectorize

  Picsart GenAI

  Converts a raster image (PNG, JPG) into an SVG vector. Auto-picks the newest enabled Picsart vectorize model unless overridden via the `model` param. Use this when the user asks to "vectorize", "convert to SVG", "make this a vector", or wants a scalable version of a logo or icon. Best results on logos, icons, and simple graphics — photographic images vectorize poorly and the user should be warned. Do NOT use this to remove the background (use `picsart_remove_bg`), replace the background (use `picsart_change_bg`), upscale a raster image (use `picsart_enhance`), or generate a new image (use `picsart_generate`). Required input: `image` — a publicly-accessible URL to a PNG or JPG (not a local file path). Optional: `model` to pin a specific vectorize model. Example: `{ image: "https://example.com/logo.png" }`. Returns `{ assets, id, model, created_at, summary, why_relevant, url, results: [{ url, metadata? }], drive? }` plus a `resource_link` block for the SVG URL (mime `image/svg+xml`). `id` is the SDK's generation handle. Clients fetch the SVG from that URL. Spends credits. Requires Authorization: Bearer <picsart_token>.

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• picsart_generate

  Picsart GenAI

  Runs any Picsart AI model end-to-end to produce an image, video, or audio result. Spends credits. Recommended flow: `picsart_list_models` to pick the model → `picsart_model_params` to learn its inputs → `picsart_preflight` to validate the payload and quote cost → `picsart_generate` to actually run. Do NOT use this for editing operations that have dedicated tools — background removal (`picsart_remove_bg`), background replacement (`picsart_change_bg`), upscale / enhancement (`picsart_enhance`), or raster-to-SVG conversion (`picsart_vectorize`). Also do NOT use it to validate params, quote cost, or browse the catalog — those are separate tools above. Required inputs: `model` (id) and `prompt`. Model-dependent optional inputs: `duration` (video seconds), `aspectRatio` (e.g. "16:9", "9:16", "1:1"), `resolution` (e.g. "1080p", "4k"), `count` (1–8 outputs), `quality`, `style`, `negativePrompt`, `imageUrls` (for image-to-X models), `videoUrl` (for video-to-X), `enhancePrompt`, `generateAudio`, and `extra` — a free-form record for model-specific params (discover them via `picsart_model_params`). Example (image): `{ model: "flux-2-pro", prompt: "a cat in a hat", aspectRatio: "16:9", count: 1 }`. Example (video): `{ model: "kling-v3-pro", prompt: "a cat skiing down a mountain", duration: 5, aspectRatio: "16:9" }`. Returns `{ assets, id, model, created_at, prompt, summary, why_relevant, url, results: [{ url, metadata? }], drive? }` in structured content, plus one `resource_link` block per result URL — image models emit image links, video models emit video links (mime `video/mp4`). `id` is the SDK's generation handle; `metadata` may include model-specific tags (e.g. `exploreImageId` for Recraft Explore models). ChatGPT renders images and videos with the Picsart media gallery UI; clients fetch the assets from URLs, never base64. Spends credits and writes to the user's Picsart Drive when the Drive option is enabled. Requires Authorization: Bearer <picsart_token>.

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• axint.schema.compile

  Axint

  Compile a minimal JSON schema directly to Swift, bypassing the TypeScript DSL entirely. Supports intents, views, components, widgets, and full apps via the 'type' parameter. Uses ~20 input tokens vs hundreds for TypeScript — ideal for LLM agents... Use: use for token-light JSON-to-Swift generation; use compile for full TypeScript DSL control. Effects: read-only Swift generation; writes no files and uses no network.

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• videos_generate

  dialogbrain

  Generate a short video (5-10s) from a text prompt using BytePlus Seedance. Optionally accepts up to 12 image file IDs from the user's attached files (visible in the [ATTACHMENTS] block) as `reference_file_ids` for style and composition. Returns immediately with a job_id; the video is delivered back via continuation when the job completes (~30-90s for fast model, ~2-5min for pro). Reference images are temporarily re-hosted on a third-party CDN (imgbb) for the duration of generation and deleted on completion — don't submit confidential references. Gated behind a workspace opt-in flag.

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• design_session

  Colour Memory

  One-call compound tool. Submit a concept, medium, audience, and constraints — receive a complete design package: historically grounded palette, cultural narrative, commercial paint matches, WCAG accessibility check, illuminant behaviour, and a ready-made image generation prompt. Replaces chaining query_conceptual + palette_from_concept + colour_story + match_paint_system + accessibility_check + get_colour_metrics. Use when an AI agent or user needs a complete, deployable colour direction in a single call. Not for iterative refinement — use individual tools for that.

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• list_images

  Goodeye

  List hosted images owned by the caller, with optional filters. ``source`` filters by upload origin: ``"upload"`` for directly uploaded images, ``"generated"`` for images created via the image generation tools. Omit to return all sources. ``visibility`` filters by access level: ``"public"`` or ``"private"``. Omit to return both. Pagination: pass ``next_cursor`` from a previous response as ``cursor`` to retrieve the next page. Returns ``{items: [...], next_cursor: str | null}``.

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• aetherwave_list_image_models

  AetherWave Studio

  Returns every image-generation model AetherWave supports, with its credit cost, default aspect ratio, supported inputs (T2I vs I2I), and any model-specific options. Call this before generate_image when you don't know the right model ID. The model key (e.g. 'grok-imagine-t2i') is what you pass as `model` to generate_image.

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