"Tools for Creating Game Character Images and Removing Backgrounds" matching MCP tools:

• upload_file

  BorealHost

  Upload a base64-encoded file to a site's container. Use this for binary files (images, archives, fonts, etc.). For text files, prefer write_file(). Requires: API key with write scope. Args: slug: Site identifier path: Relative path including filename (e.g. "images/logo.png") content_b64: Base64-encoded file content Returns: {"success": true, "path": "images/logo.png", "size": 45678} Errors: VALIDATION_ERROR: Invalid base64 encoding FORBIDDEN: Protected system path

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• studio_options

  agentee

  START HERE for any custom-print request: the menu of generation choices (print placements with plain-language descriptions, products, backgrounds, engines+costs). Present these to the human — at minimum ask which PLACEMENT and which PRODUCT they want — before calling studio_generate.

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• generate_illustration

  Logospell

  Generate a single composed illustration from a prompt - a scene, environment, hero image, banner, character portrait, or any standalone picture. (For a SET of separate isolated subjects sharing one style - icons, sprites, asset packs - use generate_image_set for solid-color backgrounds, or generate_transparent_image_set for transparent backgrounds, instead.) Returns a zip download URL: the image plus a prompt.json recording what you asked for, plus an index.html viewer. Each call costs 1 credit. Run generation calls sequentially, never in parallel - only one generation runs at a time per API key. The prompt describes the picture and is used as written (no template, no appended instructions); do not put the pixel size in it - put the size in the width and height arguments. width and height must be one of the supported pixel pairs below; any other pair is rejected. These are the maximums offered - nothing larger is available. Each line is one shape: the first pair is that shape's largest size, the rest are exact proportional downscales of it. 2816x1584, 1408x792, 704x396 2048x2048, 1024x1024, 512x512, 256x256 1456x2912, 728x1456, 364x728 3200x1440, 1600x720, 800x360 2912x1456, 1456x728, 728x364 1664x2496, 832x1248, 416x624 2496x1664, 1248x832, 624x416 1776x2368, 888x1184, 444x592 2368x1776, 1184x888, 592x444 1584x2816, 792x1408, 396x704 1440x3200, 720x1600, 360x800 Formats: png (default, lossless), jpg, webp. quality (1-100) applies to jpg and webp; default 90. Prompt max length: 2500 characters. A prompt that does not describe a picture is rejected. unpackTo: a directory on your local filesystem to extract the downloaded zip into. filename: name for the image file inside the zip (default illustration.<ext>). If a "Rate limit exceeded" error is returned, wait the suggested number of seconds before retrying. Do not retry immediately.

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• update_listing_images

  Teppek

  Add and/or remove photos on one of the USER'S OWN existing listings (max 6 total). First call request_image_upload for each new image and upload the bytes, then pass the returned keys in `add`. Adding any image re-triggers AI moderation — the listing returns to 'pending' until the new images are cleared; removing images does not. Free (no credit).

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• createImage

  Ludo AI Game Assets

  Generate game-art images from a text prompt alone, selecting an image_type (e.g. sprite) and optionally art_style, perspective, and aspect_ratio. Synchronous: the call blocks until generation finishes and returns an array of image results, each with a url; request n (1-8) to control how many variations come back. Because it generates purely from text it takes no source image, so there is no upload size limit to trip. Credits are charged only on success, scaled to the number of images produced. Use createImage to make new images from scratch; use generateWithStyle to match a reference image's art style, editImage to modify an existing image, and removeBackground to cut out a subject. Pass an optional request_id to tag the results so you can retrieve them later via getImageResults. Requires an API key (user scope). Credits: This endpoint consumes 0.5 credits per result.

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• rack_redundancy

  eurorack

  Call this when the user asks what they can SELL, remove, downsize, or trim — "what can I sell?", "which modules are redundant?", "what's doing double duty?", "I have too many modules, what can go?", "what's not pulling its weight?". The inverse of reachable_techniques: where that adds, this prunes. Given the user's COMPLETE rack, it runs a leave-one-out over the same technique matcher reachable_techniques uses — for each module, does removing it cost any currently-reachable technique? Returns three buckets plus the overlap map: - load_bearing: removing the module drops ≥1 reachable technique → KEEP. `sole_filler_for` names the techniques it props up. - sell_candidates: removing it drops nothing AND another rack module covers the same function → the first place to look. `overlaps` names the shared function and `also_provided_by` the other providers. - utility_or_uncovered: removing it drops nothing and nothing else does its job — it fills no catalogued technique role (usually a mixer / VCA / I/O / mult) OR serves an idiom the corpus is thin on. Judge by hand; this is NOT "sellable". - overlap_map: every function ≥2 of the rack's modules provide (the "you have three reverbs" view) — the evidence behind sell_candidates. IMPORTANT — this is decision-support, not a verdict, and the limits bite here: - cardinality is NOT counted: a 2nd VCA / envelope / mult reads "redundant" though real patches use both at once. Overrule the tool on utilities. - only the curated catalog is seen: a module serving an under-covered genre looks redundant when it isn't. - two modules covering the same role are BOTH flagged — you can usually drop only one. - it cannot weigh sonic character, ergonomics, or sentiment. Trust it most for specialized overlap (e.g. several reverbs); present results as candidates to weigh, never "sell these". Pass the COMPLETE rack — the server is stateless and a partial rack distorts the analysis. Args: - rack (string[], required): module ids, e.g. ["make-noise/maths", "intellijel/quad-vca"]. Max 64. Unknown ids are returned in `unresolved` (with did-you-mean), not silently dropped.

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• move

  cnvs.app

  Reposition an existing item to a new (x, y) without retyping its content. Works for every item kind: `text` and `link` set the top-left to (x, y); `line` translates every point so the stroke's bounding box top-left lands at (x, y); `image` sets the top-left like text. `kind` defaults to `text` for backward compat with older callers. Find the id + kind via `get_board`. Prefer `move` over re-creating an item when only the location changes — it preserves the id, content, author and avoids a round-trip of base64 bytes for images.

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• generate_clips

  Recao

  Render UGC video scenes as ad-ready clips, metered per second of video (the estimate shows the exact price before anything renders). Pass 3 to 6 scenes (5 to 8 seconds each, one action per scene, spoken lines at most 20 words; empty spoken_line for silent characters). Consecutive scenes pack into single TAKES of up to 15 seconds, one generation each. HOW CHARACTER IDENTITY WORKS, read carefully: all characters are described in TEXT (avatar_id resolves to its persona brief; or write the persona field yourself, covering one character or a whole ensemble). The video model rejects every image that contains a person, so no photo can anchor a face. Text keeps a character IDENTICAL only WITHIN a take; ACROSS takes it preserves the look and styling but the exact face can drift, and neither avatar_id nor persona prevents that. Structure your script so scenes where the same character must be recognizably identical sit adjacent and fit one take (15s or less); treat cross-take appearances as different shots of a matching character, and review the result. reference_image_urls (up to 9 https images) keeps real products or props on-model in every take; these images must contain no people. Without confirm, it validates the contract and returns the per-scene price estimate in EUR, and makes nothing. With confirm=true it starts the metered render and returns a job_id: rendering runs in the background over a few minutes, so poll clips_status with that id to get per-scene clip URLs plus the uncut takes. Paid plans only.

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• generate_style_template

  framesail

  Render one of a style's two template images — a REAL step of style setup, not an optional extra: a style isn't finished until both its character and environment templates are rendered (the app shows them on the style card). Asset reference images render against them (characters → character template; environments and objects → environment template), and segment renders fall back on them when a shot has no asset reference — so finish BOTH before generate_asset_reference. Run once per template_type ("character" | "environment") for every new style; skip types the style already has (get_style's `templates`). A template already exists is a hard stop here — the call refuses unless replace=True, because overwriting one silently re-anchors every future render. Async — await_jobs(style_id=...), then get_style.

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• create_reference

  Logospell

  Create an upload slot for a reference image. Returns an upload URL and a ref_ token: upload the image file with one shell command (curl -T <file> '<uploadURL>'), then pass the ref_ token to the reference-image parameter you are filling - every parameter that takes reference images names this tool in its description. This is the ONLY way to supply reference images, and those parameters accept ref_ tokens and nothing else. Image data never goes inside a tool call: a call is JSON, so an embedded image would have to be base64 text that you, the caller, must emit character by character - slow, error-prone, and enough to exhaust your context window. The upload moves the bytes out-of-band instead: a plain HTTP PUT of the raw file, so any HTTP client works; if your environment has no way to send one, install curl. And when the image you want is from one of your OWN recent Logospell generations, skip the upload entirely: pass sourceGeneration and sourceImage and the server copies it directly - the shortcut for extending an existing set in its own style. Accepts PNG, JPEG, or WebP, each at most 500KB, each side between 64px and 768px - resize before uploading if needed; larger reference images do not improve results. A reference is private to your API key and can be used in any number of later calls; its expiry window restarts each time you use or re-upload it, so uploading a few references once can serve a whole session of work. Costs no credits.

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• generate

  designforyou

  Generate one or more finished images from a template (get a template_id from recommend_template or browse_templates) plus a description. Use this after the user has selected or explicitly supplied a template_id; otherwise call `recommend_template` first so the visual gallery can collect the selection. Works for all categories (Instagram, logo, app-store, Visual Novel backgrounds/sprites, CG illustrations). Pass variants for multi-image output (expressions, time-of-day, etc.). Pass session_id to refine a prior result. Pass context_ids to ground a new image on prior designs (character consistency for VN CG scenes). Set model to 'minimax-h3-image-balanced' or 'minimax-h3-image-quality' (or use the 'h3 balanced'/'h3 quality' aliases) to render through the MiniMax H3 image service; context_ids are forwarded as ordered H3 reference images.

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• clipform_generate_video

  Clipform

  Generate a video from images, video clips, or both, synced to an audio track. Use this for narrated question backgrounds, topic visualisations, or any form node that benefits from video. Combine with clipform_generate_tts for narrated audio and clipform_search_media for royalty-free images. Creates 9:16 (720x1280) with Ken Burns pan/zoom effects and transitions. Returns a public URL when complete. Items: type "image" (Ken Burns motion) or "video" (cover-cropped, muted by default). Duration matches audio_url or set duration_seconds explicitly. For multi-question builds, pass wait: false on every render: each call returns a job ID immediately, so all renders run in parallel - then collect URLs with clipform_check_render. Sequential waiting renders take 15-120 seconds EACH. Choosing a render tool: for a recognisable form/quiz beat (guess-the-city, this-or-that, mystery reveal, multiple choice, photo montage...) reach for a video template first (clipform_list_video_templates + clipform_render_video_template) - it is a one-call recipe. Use clipform_generate_video for a narrated or audio-synced media montage (images/clips timed to a voice track). Use clipform_render_composition only when neither fits and you need a custom layer stack. Montage disambiguation: choose clipform_generate_video when the montage is narrated or synced to an audio track; choose the slideshow video template when it is silent (motion + transitions only, no voice-over). A render for a form node is not done until it is attached to that node. Pass node_id (and form_id) so the completed render attaches itself automatically - do not poll clipform_check_render to completion or manually chain clipform_upload_media_asset + clipform_attach_node_media; fire the render and move on.

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• create_game_draft

  publish

  Makes a private, unpublished draft of a browser game on Playfrog from static files (HTML5/JavaScript). Nobody can see it or play it, including by direct link, and the response carries no play link because nothing serves the game yet. Covers requests to publish, share, post, put online, put on the internet, or host a browser game someone made, and requests for a link other people can play. Send the game files; an index.html at the top level is required, 2.5 MB of files in total. An optional cover image improves the game page and social share card. Returns claim_url, the one link that publishes the game: publishing requires a free Playfrog account, and the game becomes public only after a person opens that link, signs in or creates an account, and finishes publishing. An unpublished draft is deleted after 7 days. update_game_draft replaces the files of a draft made in this same connector session. Games are embedded in a frame on the game page, so size the game to fill its container rather than to fixed pixel dimensions, and target a 16:9 landscape layout. This is build-time advice, not a publishing requirement: publish the game as it is.

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• removeBackground

  Ludo AI Game Assets

  Remove the background from a single image, returning the subject isolated on a transparent background. Supply the source image (URL or base64); optionally set crop to trim the result to the content, and creative_edit (default true) for higher-quality output that may not match the input pixel-for-pixel. Synchronous: the call blocks and returns a single image result with a url (not an array). The image is uploaded and validated, and an image larger than 15MB is rejected with HTTP 400. Credits are charged only on success. Use removeBackground for this dedicated cutout task; editImage can also remove backgrounds via a prompt but is better for broader edits, while createImage and generateWithStyle produce new images rather than process an existing one. Pass an optional request_id to tag the result so you can retrieve it later via getImageResults. Requires an API key (user scope). Credits: This endpoint consumes 0.5 credits per result.

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• game

  Cheapshark

  Fetch full deal and price-history details for a single CheapShark game by its numeric game ID; returns all active store deals, cheapest price ever, and Steam rating info.

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• clipform_search_media

  Clipform

  Search images or stock video clips. Pass one query or many (max 10) - multiple queries run in one call instead of separate tool calls. Use results to feed into clipform_generate_video for narrated slideshow videos, or upload directly as still images via clipform_upload_media_asset then clipform_attach_node_media. All results are pre-cleared for commercial use. Results include a description (alt text where the provider has it) - use it to pick visually distinct images. Example: { queries: [{ query: "saturn rings" }, { query: "mars surface", count: 3 }] } returns portrait images for both.

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• create_inference

  Retro Diffusion Pixel Art MCP

  Generate images using the public /v1/inferences endpoint. For the highest quality prefer RD Pro styles (rd_pro__*); they support reference_images for character/style consistency. For animation styles prefer start_inference_job + get_inference_job instead — animations are long-running. Use `input_image` for the main source image, `reference_images` for extra per-inference guidance, and `style_reference_images` only on create_user_style/update_user_style. The response excludes raw base64 image payloads to keep MCP outputs compact.

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• legends_get_game

  Legends of Learning

  Fetches the full public detail for one Legends of Learning game by its numeric id (from legends_search_games). Returns the game's id, title, description, image, estimated_duration in minutes, type, grades served, teacher/student ratings, instructions, vocabulary, discussion questions, capability flags (supports_ipad, supports_tts, multi_language, saves_progress), lexile_level, the public url, and `learning_objectives` — the standards the game is aligned to, each with id, title, code, and standard_set. Example: {"game_id": 1445} returns that game, or an error result if no such game is publicly available.

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• list_servers

  mcp

  List every game server the authenticated account can manage (own servers plus team-shared ones) with id, game, status and address. Call this first to discover server ids for the other tools.

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• generate_image

  switch

  Generate one or more Switch images. Auto-routes to the right model based on subject (Nano Banana 2 default, GPT Image 2 for swimwear/beach, Switch Model/Ultra/Pro for sexier content, Nano Banana Pro for typography-heavy). Counts <= 8 render inline in chat; counts > 8 queue to your Switch Studio with progress polling. All images persist to your Studio library and folder. Pass an optional `style` (e.g. "wellness/warm_amber_tropical", "high_fashion_editorial/testino_glossy", "movie_scene/neon_noir_action") to apply a curated photographic stack from the apply_* skill tools.

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