"Basic Image Editing Operations like Resizing, Cropping, and Blurring" matching MCP tools:

• 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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• 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` (1–10 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: "1:1", 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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• get_site_info

  Bogeyland

  Returns basic information about this neighborhood directory: name, locale, domain, description, canonical URLs for key sections, plus the current LOCAL TIME and CURRENT WEATHER at the neighborhood (temperature, condition). Use this for any "what time is it there" or "what's the weather like" context.

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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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• list_sheets

  Bilig WorkPaper

  Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.

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• niche_reuse_asset

  Niche — Editorial Intelligence

  Copy an image that already exists on one output onto another cell, instant and free (no regeneration, no credits). Use this when the user wants 'the same image' on a second surface ('use the LinkedIn image on X', 'same picture on the newsletter') instead of niche_render_image_card (which generates a new image and costs credits). Both cells must already exist on the session (add the target via niche_add_output first if needed) and the source must have a rendered image. Copies the source's static_urls onto the target so it publishes with that image. Idempotent: source==target is a no-op.

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• list_workflows

  Dreamlit

  Read-only. Use to find workflows in a project by name, description, or trigger type before inspection or editing. Trigger filters include database, auth email, repeating, broadcast, and no-trigger workflows. Returns paginated workflow summaries, published/sandbox state, trigger type, workflow URLs, totalCount, hasMore, and nextOffset. Do not use as the final source of truth before editing; call get_workflow_and_preview_url for full structure.

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• contract_amend

  shiply

  Create an amendment to a SIGNED parent contract. Scope delta required; fee delta and target date optional. Returns the draft amendment for editing before send — call contract_send with the returned amendment id to fire it. Cannot amend an amendment (amend the parent instead).

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• render_dxf

  aspicio-dxf-viewer-remote

  Render a DXF drawing to a PNG image you can look at. Use this to answer visual questions (what does it look like, where is a feature) — it returns an image, not text. For structural facts and measurements, prefer describe_dxf; never measure pixels. Some chat UIs do not display the returned image to the user: for URL sources the result also includes a direct image link — show it to the user (e.g. as a markdown image) when they need to see the render. When the user wants to see or explore the drawing themselves, prefer view_dxf (interactive viewer) — if your platform gates it behind user approval, offer it and ask rather than substituting a static render.

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• lamina_generate_image

  lamina

  Dispatch a single atomic image generation. Sibling of `lamina_create` (the agentic router) — use this when you already know which model fits, or when no app fits the brief. WORKFLOW: (1) `lamina_models_list({ modality: "image" })` → pick a model. (2) `lamina_models_describe({ modelId })` → read its flat `paramSchema`. (3) `lamina_generate_image({ model, prompt, params })` → dispatch, get runId. (4) `lamina_status({ runId, wait: true })` → poll until completed; the response has `output.url`. ONE TOOL, BOTH OPERATIONS: • Text-to-image — call with just `prompt` (and any text-mode params). The model id you picked is the only thing that selects the operation. • Image-to-image (edit / remix / background-swap / etc.) — call the same tool, but include a source image in `params`. Hybrid models (nano-banana-pro, gpt-image-2, gemini-2.5-flash-image, seedream-4.5, flux-2-flex, nano-banana-2, gpt-image-1, gpt-image-1.5) flip to image-to-image automatically when `params.imageUrls` is a non-empty array (or `params.imageUrl` is set for single-source models like flux-pro-kontext). Edit-only models (bria-bg-remove, ideogram-character, ideogram-v3-remix/reframe/replace-background, flux-pro-kontext, ideogram-character-remix) only have image-to-image — `params.imageUrls`/`imageUrl` is required. INPUTS: • `model` (required): a model id from `lamina_models_list`. Don't invent it. • `prompt` (required for most models; check `paramSchema.prompt.required` from `lamina_models_describe`; absent from `paramSchema` for prompt-less models like `bria-bg-remove` and `ideogram-v3-reframe`): natural-language brief; ≤2000 chars. • `params` (model-specific): every key MUST be declared in the chosen model's `paramSchema` (call `lamina_models_describe` first). Unknown keys are rejected with a structured `invalid_params` error; each error has `field` + `allowed`/`range`/`got` so you can correct on retry. Omitted optional keys fall back to schema defaults. • `webhookUrl` (optional): HTTPS URL. On terminal status Lamina POSTs `{runId, status, model, prompt, resolvedParams, output, errorMessage, completedAt}` HMAC-signed. RESPONSE: `{runId, status: "queued"|"completed", model, mode, prompt, resolvedParams}`. `mode` is the resolved value ("text-to-image" | "image-to-image"). The `runId` is the fal_request_id — pass it to `lamina_status`. SYNC vs ASYNC: identical contract. Vertex-backed models (`imagen-4.0-*`, `gemini-2.5-flash-image`) complete in seconds and return `status: "completed"` on the first poll. fal-backed models queue and take 5–60s. `lamina_status({ wait: true })` handles both transparently. ERROR HANDLING: validation failures return `code` + `details.errors[]` with `field` + `error` + `allowed`/`range`/`got`. Common codes: `model_not_supported`, `mode_not_supported`, `invalid_params`, `dispatch_failed`.

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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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• aetherwave_edit_image

  AetherWave Studio

  Edits an existing image guided by a text prompt. Pass a public `imageUrl` plus a `prompt` describing the change ("add a moon to the sky", "swap the background for a neon city", "make it look like a comic panel"). Submits, polls, and returns the edited image URL(s). Default model is 'grok-imagine-i2i' (6 cr per call, returns 2 variations, ~30s, best cost-to-quality on standard edits). Other I2I-capable models: 'seedream-v4-edit', 'wan-2.5-spicy-i2i', 'flux-kontext-pro', 'qwen-image-edit', 'gpt-image-1.5-i2i' (slow, ~5min). Use list_image_models for full lineup. Note: source URLs with spaces or parentheses may fail upstream; prefer clean URLs. ## Model selection guide for edits Default: `grok-imagine-i2i` (6 cr per call, returns 2 variations = 3 cr/image effective, fast ~30s, strong general-purpose edit quality). Pick a different model when: - Need a single deterministic output, or 4K resolution -> `seedream-v4-edit` (7 cr per image, supports 1K/2K/4K, multi-image up to 6) - Subtle edits / preserve composition / character consistency -> `flux-kontext-pro` or `flux-kontext-max` - NSFW edits -> `wan-2.5-spicy-i2i` - Highest quality, time is not a concern (~5 min OK) -> `gpt-image-1.5-i2i` or `grok-imagine-quality-i2i` (16 cr @ 1K, 22 cr @ 2K) - Stylized / artistic transformation -> `midjourney-i2i` If the user simply says "edit this image" with no other signal, default to `grok-imagine-i2i`.

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• get_asset_pack

  Mozaika

  Get a ready-made AI-generated icon pack (12 consistent icons) — e.g. a house style like 'clay-starter' / 'line-minimal-starter', or a pack generated in the MEASURED style of a decoded brand. Free and unmetered. Each image is a 1024px transparent PNG you can download and use directly (full commercial rights). Unknown slug → lists available packs.

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• list_api_reference_pages

  docs-mcp

  List pages in Redpanda API reference documentation. Returns endpoints, schemas, and topic pages with URL, title, type, and description. SCOPING (important for accurate results): - api="all" or omit: Lists all available APIs - api="admin": Cluster management operations (brokers, partitions, configs, users) - api="cloud-controlplane": Redpanda Cloud resource management (clusters, networks, namespaces) - api="cloud-dataplane": Cloud cluster data operations (topics, ACLs, connectors) - api="http-proxy": Kafka operations over HTTP (produce, consume, offsets) - api="schema-registry": Schema management (register, retrieve, compatibility) Use this to browse API structure. For general Redpanda docs, use ask_redpanda_question instead.

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• open_in_editor

  clipkit

  Validate the current project and create a link that opens it in the Clipkit web editor, where the user can preview and refine it. This shares the PROJECT (nothing is rendered — that's render_video). Use after composing or editing. Returns a URL.

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• oj_capabilities

  Codeforces MCP Server

  Report audited Codeforces official API capabilities and unsupported operations.

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• search_google_ads

  Hermoso

  Structured Google Ads Transparency pull for ONE advertiser (by domain or advertiserId) — use when you know the brand; use research_ads for open-ended research. Deliberately fetches the cheap BASIC listing (get_ad_details=false, ~1 credit — the detailed variant with per-ad headlines costs 25 credits/call and is not exposed here). Returns compact JSON {advertiser, format, adUrl, image, firstShown, lastShown} per ad.

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• set_product_image

  Hermoso

  Lock an image as the ad's real PRODUCT photo so every render grounds on the true packaging. Pass `imageUrl` = a product shot's URL — an image from a prior research result (an organic Instagram/TikTok post, a scraped page image), a workspace / list_product_photos url, or any public product photo. The server downloads it and runs a product+safety check: a lifestyle/scene shot with no clear product, or an off-category / unsafe image, is REJECTED and NOTHING is locked (the summary says why). On PASS it persists the photo to a DURABLE url and returns it — pass that url as a reference to generate_image / render_ad. Bills one vision check. Reads YOUR saved brand for the category match (pass brandId to target a specific brand — switches this key's active brand like use_brand).

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• get_services

  turva-mcp

  Returns turva.dev's service catalog: agent-readiness audit, advisory, implementation, agent operations, and MCP server design, plus the engagement model and pricing (fixed list prices for audit, advisory and implementation; agent operations and MCP server design on request). Use this when a user asks what turva.dev offers, what it costs, or how an engagement works. Read-only: returns static JSON and changes nothing.

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