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

• get_design_guidelines

  Marmo UI MCP

  MANDATORY FIRST CALL before writing any @marmoui/ui code in this session. Returns a step-by-step generation checklist (which tools to call, in what order), critical rules (no namespace sub-components, PageSection is self-closing, no Sidebar export), component patterns, and ICON LIBRARY RULES. Pass iconLibrary (default "phosphor"; also "material" | "lucide" | "tabler" | "heroicons" | "feather") to get that library's import source, icon name map, and weight/style mapping — and pass the SAME value to review_generated_code so it enforces it. Ask the user which icon library they want before writing UI code. Call topic="patterns" to get the generation checklist specifically.

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• remix_static

  Hermoso

  One-click STATIC-AD REMIX: rebuild a competitor/reference STATIC (image) ad as an on-brand version — SAME layout, composition and energy, but YOUR product, brand colours, logo and voice, with every trace of the source brand removed. Pass `imageUrl` = the static ad image to remix. Uses your saved brand (pass brandId to target a specific brand — that switches this key's active brand like use_brand). IMAGES ONLY — for video ads use render_ad. Bills as one image generation.

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• generate_video

  BananaBanana Image & Video Generation

  Start an AI video generation (Google Veo 3.1 family or Gemini Omni Flash). EXPENSIVE: $0.10–$4.40 per clip. Cost confirmation is mandatory: the first call always returns a USD quote and charges nothing — repeat the call with confirm_cost set to the quoted amount to actually start. Returns a job_id; poll get_result (videos take 1–10+ minutes). Failed generations are auto-refunded. Models: veo-3.1-fast (default, good quality/price), veo-3.1 (best Veo quality), veo-3.1-lite (cheapest, 720p/1080p), omni-flash (always has sound, any duration from 3 to 10 s at $0.10/s, supports conversational editing via edit_from_generation_id). Image inputs: first_frame animates a still picture, reference_images keep a subject/style consistent — both accept a job_id of a completed image generation on this account or a public image URL, and on omni-flash they can be combined (up to 10 images total). Example: {"prompt": "drone shot over a misty pine forest at sunrise", "model": "veo-3.1-fast", "duration": 8, "resolution": "720p", "confirm_cost": 0.70}

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• verify_content_credentials

  Lumethic Photo Verification

  Verify a single image's authenticity — use this when you only have the image and no RAW camera file. Checks its embedded Content Credentials (C2PA) for capture provenance and AI-generation flags, and runs advisory forensic screens (error-level analysis, double-JPEG artifacts, EXIF timestamp consistency, editing-software traces, screen recapture). Free: it does not consume your verification quota. Provide the image inline as image_base64, or — for large files — call create_verification_upload and pass the returned image_object_key. Returns a verification id; poll get_verification, which on completion includes a structured evidence_report (verdict, per-check findings, coverage). Works without an API key on the keyless anonymous tier (rate-limited; returns an anonymous_user_id to reuse). For the strongest forensic check, use verify_photo with a RAW + JPEG pair instead.

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• get_uploaded_image

  GlanceAI Fashion MCP

  Retrieve the image the user most recently uploaded via the `upload_image` tool as an image block for analysis. WHEN TO CALL: Immediately after the user confirms their upload (message says 'Image uploaded successfully'). WHAT TO DO AFTER: Analyse the image and continue the original flow — describe what you see, extract style/colour/product details, and use that information to fulfil the user's request. Never wait for further instruction before analysing.

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• propose_montage

  Uwear

  ONLY for video montage/stitching/export workflows. Use when the user explicitly asks to create a montage, stitch clips, make a reel, export a video sequence, make video clips from images, or combine images/videos into one final video. Never use this for a photoshoot, lookbook, product shoot, collection shoot, outfit shoot, garment shoot, or image-generation request; those must use request_user_context followed by propose_brief/update_brief. Do not call this merely because selected context contains images, generations, garments, or models. A photoshoot may later feed a montage, but the photoshoot itself must be proposed as a BriefProposal first. PROPOSES the montage for user review — user can edit clips, generate missing videos, then export. Supports: existing videos with optional trim (`target_duration` or `start_time`/`end_time`), images that need video generation (specify video_model + a bespoke per-image motion prompt, and optionally `target_duration` or `duration`), per-clip speed/mute, global aspect ratio. If the user asks for clips to be e.g. '3 seconds each', set `target_duration: 3` on every item, including image items. For image items, avoid generic repeated prompts: tailor each prompt to the specific image and any requested zoom, movement, energy, or camera direction. If motion is not specified, inspect the image first with view_image and then write a fitting motion prompt from the image content before proposing. The user reviews and confirms in the UI. Export is free (0 credits); video generation clips cost credits per their model.

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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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• 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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• service_info

  x402image

  Free. Returns x402image service metadata and the list of paid image tools with their per-call USD prices. No payment or input required. Call this first to discover capabilities and pricing.

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• generate_stock_research_report

  hpsilab-mcp

  Full markdown research report with five stock-report charts. Pro tool ($0.35/call via x402 for anonymous callers; free within plan limits for signed-in accounts, subject to a monthly report quota). Runs analyze_stock and stock-report image generation concurrently, then renders a presentation-ready markdown report (direction, direction score, bullish / bearish factors, source-tool status, and the five chart embeds). The markdown is returned for display and the same data is mirrored in structured JSON. Signed-in hpsilab users call this within their plan's free rate limits. Anonymous / tokenless agents pay per call via x402 (USDC on Base) when payments are enabled — send the x402 payment in the request _meta. Args: symbol: Stock symbol, e.g. "RXRX". refresh: Bypass the backend's fresh IV cache for the IV-driven modules. Defaults to False. force_images: Force a fresh image render instead of reusing the backend's image cache. Defaults to False.

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• pictify_render_multi_page_pdf

  mcp

  Generate a multi-page PDF from a template by providing multiple sets of variables. Each variable set produces one page in the final document. Supports 1-100 pages per PDF. Common use cases: bulk invoice generation, certificate batches for events/courses, multi-page reports, product catalogs, and employee ID cards. WORKFLOW: Call pictify_get_template_variables first to discover available variables, then provide an array of variable sets (one per page). Returns a single combined PDF URL. For generating separate image files per set, use pictify_batch_render instead.

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• get_agent_registry

  DC Hub — Data Center & Power Intelligence

  Curated roster of the AI platforms + agent frameworks in the DC Hub agent ecosystem — each with its recommended DC Hub tools and authentication tier. Recognized MCP clients include Claude and Cursor, with Cline, Continue and other agents surfaced as they are integrated. Use it to see which platforms DC Hub supports and how to connect them. Try: get_agent_registry. NOTE: this is a curated ecosystem/capability index, NOT live per-caller call/citation telemetry. Do NOT use for platform uptime / backup health (use get_backup_status).

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• get_facets

  Besot: Musician Fashion Resale

  Return the values that actually exist in the catalogue for filtering a search: sizes, conditions, source platforms, artists, designers, and the price range. Use this before search_pieces when you want to build a precise query from real values rather than guesses. For example, to check which sizes of a garment are genuinely listed right now, or which platforms currently carry a given collection.

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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? }` as a single JSON text block plus matching structuredContent (no `resource_link` blocks — the widget is the single source of visual truth, so result URLs are not duplicated as separate content blocks). `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_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? }` as a single JSON text block plus matching structuredContent (no `resource_link` block for the SVG URL — the widget is the single source of visual truth, so it is not duplicated as a separate content block). `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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• 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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• 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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• aetherwave_list_video_models

  AetherWave Studio

  Returns every video-generation model AetherWave supports (Grok Imagine, Wan 2.7, Hailuo 02, Seedance Pro/Lite, Kling 2.6 with audio, VEO 3.1, Happy Horse, etc.) with per-second credit cost, supported durations, resolutions, aspect ratios, and whether the model needs an input image (I2V). Call this before generate_video when you don't know the right model ID.

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• agent_brief

  Colour Memory

  Generate a complete colour direction package for another AI agent or image generation model. Fetches a historically grounded archive palette from the concept, then produces: an agent brief (colour direction in prose), colour tokens with hex values and roles, a model-specific image generation prompt, a negative prompt, and lighting notes. Supports midjourney, flux, dalle, stable_diffusion. Example: task='luxury hotel bedroom', concept='Ottoman winter luxury', model='midjourney'. Use this to make Colour Memory the colour layer for other AI systems. Archive-grounded retrieval is evidence-filtered: entries with claim_role='reject' (no primary source and no period connection), stub entries, blank-source entries, and entries below minimum_claim_strength are never selected. If fewer than palette_size colours pass these filters, the call returns an honest incomplete result (ok:false, error_code:INSUFFICIENT_EVIDENCE_ELIGIBLE_PALETTE) rather than padding the palette with rejected or weak evidence. Negative constraints (from 'avoid' or negation phrases in concept like 'must never', 'without', 'not') are also applied to retrieval, not just flagged afterward -- a brief that says a wedding must never feel funereal will not surface mourning-themed colours in the first place. locked_palette calls skip evidence filtering entirely since the caller is supplying colours directly, not requesting archive evidence.

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• search_agent_directory

  TensorFeed

  Search the TensorFeed Agent Self-Directory for hireable AI agents. Filter by skill (from a controlled vocab including research, data-analysis, coding, content-writing, voice-acting, image-generation, etc), service_area (research/data/coding/writing/voice/image/video/other), language (BCP 47), availability, hourly rate cap, minimum years of experience, or verified-hireable status. Verified-hireable members (operators paying $5 USDC/30 days for top-tier visibility) sort first. Free tier capped at 25 results. Returns wallet, display_name, operator_url, skills, rates, languages, years_experience, composite reputation rank, trust grade. TF publishes self-descriptions; TF takes no fee from off-platform transactions between operators and the agents who contact them.

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