"A Model Context Protocol (MCP) server for Leonardo.ai image generation" matching MCP tools:

• 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_remove_bg

  Picsart GenAI

  Removes the background from an image, returning a transparent cutout of the foreground subject. Auto-picks the newest enabled Picsart remove-bg model unless overridden via the `model` param — no need to call `picsart_list_models` first. Use this when the user asks to "remove the background", "cut out the subject", or "make the background transparent". Do NOT use this to replace the background with a new scene (use `picsart_change_bg`), upscale or sharpen the result (use `picsart_enhance`), convert raster to SVG (use `picsart_vectorize`), or generate a new image from scratch (use `picsart_generate`). Required input: `image` — a publicly-accessible URL. Local files are not supported; if you only have a local file, first make it available as a public or app-authorized URL. Optional: `model` to pin a specific remove-bg model, `outputFormat` (e.g. "png"). Example: `{ image: "https://example.com/portrait.jpg" }`. 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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• 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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• analyze_company

  Nordic Financial MCP

  AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'

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• get_latest_render

  kernelcad

  Render a project's current model server-side and return it as an inline image so you can SEE what you built. Use this after open_in_studio (or any /p/<slug> link): call with that `slug` to inspect whether the build looks right. CRITICAL — the image is rendered from the MODEL on the server; it does NOT reflect the user's Studio camera, zoom, or screen. NEVER ask the user to rotate, zoom, pan, move the camera, close a slider, or change their view to help you see — you cannot affect their screen and it cannot affect this render. To see a different angle, call this tool again with a different `view`. By DEFAULT (omit `view`, or `view:"all"`) it returns a CONTACT SHEET of all six canonical views in one labeled image — a 3×2 grid, top row [iso, front, right], bottom row [back, left, top] — so you can judge the model from every side regardless of its orientation (e.g. to find which side has the doors). Pass a single `view` (iso/front/back/left/right/top) for one large render of that angle. DETERMINISTIC: the same model + view always returns the same bytes — identical bytes are NOT a stale/lagging snapshot. If you changed the model, push it with open_in_studio FIRST, then re-render to see the change. The image is always current and never a blank capture. Colors and shading match Studio (same palette / base-material color). The slug is the capability: no OAuth for public/unlisted; private projects require the owner signed in. The PNG is base64-inlined as a real image block by default; pass `paths_only: true` for metadata only. No renderable geometry or a mesh failure → { ok: false, error, hint }, never a blank image.

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• niche_attach_image

  Niche — Editorial Intelligence

  Upload or attach a user-supplied or externally-designed image (bring-your-own asset) to a post: the creator's own visual (a product shot, their actual work, a card designed elsewhere) instead of an AI-generated image (niche_render_image_card photo, paid) or a flat brand card. Free, with no image-generation spend. For a visual-product maker the real piece is the sale. Input modes, in order of preference: (1) `upload_ref`, the FAST path for an agent that built the asset itself and can run a shell: POST the raw file to `/asset/upload` (multipart/form-data, your bearer token) to get back an `upload_ref`, then pass it here. The bytes travel over HTTP and never round-trip through the model as base64, so it's effectively instant for a real graphic. (2) `image_url`, a fetchable https URL (the server fetches + stores it; for an asset that already lives on the web). (3) `image: {mime_type, data_base64}`, inline base64, fine for small images only. (4) `image_chunk`, the no-shell FALLBACK: upload bounded chunks of base64. It still re-types the bytes through the model (slow), so use it only when the agent has no shell to curl with. Split the file's bytes into ~32-48KB pieces, base64 EACH independently, send in order, each with a `sha256` of that piece's raw bytes so the server catches a mis-transcribed chunk and has you resend just that one (this is what makes the slow path reliable). Omit upload_id on the first chunk; the response returns one to pass on the rest. Set `final:true` on the last chunk (optionally with `total_sha256`); that call assembles, validates, and attaches. The cell's output must already exist (use niche_add_output first if needed). Sets it as the post's image; publishes with the caption. A dimension_note warns if the image's aspect won't fit the cell. Undo-able (the prior image is kept in history).

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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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• deploy_image_generator

  Goodeye

  Deploy a reusable image generator that skills 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. Skills 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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• 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, audio, or text 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). Text/LLM models (mode "text" in the catalog — e.g. gemini-3-pro, gpt-5.5, claude-*) run synchronously (`async` is ignored) and return the generated text as the text content block plus `text` in structured content. 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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• 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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• 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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• generate_and_attach_image

  Caulo

  Generate a NEW image from a text prompt via the platform's allowlisted image-gen provider (currently OpenAI gpt-image-1) and return an asset_id ready to attach to create_post / add_comment / send_dm. Requires the separate `media_authored` scope — granting `post` alone does NOT permit AI image generation. The user must have ticked the box on caulo.ai/settings/agents. Pipeline: caulo.ai's /api/media/generate calls the provider server-side, gets PNG bytes, runs them through the SAME /sign + /finalize Tier 0 / Tier 1 / Tier 2 moderation pipeline that protects human uploads (EXIF strip, polyglot neutralization, perceptual-hash kNN, Haiku Vision for CSAM / NSFW / rule violations). A rejected generation is the moderation pipeline doing its job — relay the reason to the user; reword the prompt if you retry. Provenance: every asset created via this tool carries `provenance='agent_authored'` and `generator_model='gpt-image-1'`. The image itself carries a persistent AI-generated marker — surfaced in the data (`media_ai_generated[]`) and rendered as a chip ON the image everywhere it shows. This does NOT change the post's text badge: a human-written post you illustrate with a generated image stays `human`, the image is marked AI. The two axes are independent — text authorship vs synthetic media (db/64). C2PA cryptographic preservation is NOT yet implemented (see SESSION_HANDOFF §10 backlog). Returns { asset_id, status: 'approved' | 'rejected', nsfw_level?, generator_model }.

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• generate_deck_image

  tela

  Generate an image from a prompt and attach it to a deck page (editor+), ready for a bg:/image: slot. Returns the serve URL + a  snippet; reference it by path (don't regenerate on re-render). Read the imagery module first (deck_authoring_guide module="imagery"): most slides need NO image — use it for atmosphere/concept/focal only, reuse ONE background, write rich on-palette prompts, and prefer images raw. May be unavailable (503) if the instance hasn't configured image generation or AI is paused; generation can take from ~20s to a few minutes depending on the model.

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• list_models

  BananaBanana Image & Video Generation

  List all available image and video generation models with current per-unit USD prices, supported resolutions, durations and constraints. Prices come from the same source as the website — call this before quoting costs to a user or choosing a model. Free, no charge.

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• alldomains_resolveDomain

  SAP MCP Server

  Resolve a multi-TLD domain to its owner wallet. SAP MCP context: Protocol alldomains; operation class read. Use to resolve an AllDomains name without changing ownership or records. Use only when the requested name service is not SNS-specific.

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• read_docs

  clipkit

  Return a canonical Clipkit doc as text. topic "agents" = the authoring guide (schema cheat sheet, pattern catalog, recipes, guidance — read this BEFORE composing); "protocol" = the formal field spec; "brand" = brand reference. (Same docs offered as MCP resources, exposed as a tool so you can read them directly — resources are not always model-readable.)

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