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668,978 tools. Updated 2026-10-17 08:42

"Nano" matching MCP tools:

  • Is this backtest winner real, or just the best of N tries? The multiple-testing selection correction (family-wise p) in one $0.01 call — verdict NO or PROVISIONAL. Use when your agent has a backtest winner, a research result, or any return series that looks good — and needs the cheapest possible check on whether it is real or the luckiest of N tries. One call runs the selection correction: the family-wise p of the series' own t across your declared n_tested. V PAID: $0.01 USDC on Base via x402. Call it to receive the payment challenge. Example request: {"returns": [0.8, -0.3, 1.2, 0.5, -0.6, 0.9, 0.4, -0.2, 1.1, 0.7, -0.4, 0.6, 0.3, -0.5, 1.0, 0.8, -0.1, 0.5, 0.9, -0.3], "n_tested": 20}
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  • Generate media with ANY Media Forge model (full catalog — Seedance, Kling, Veo, WAN, Flux, Nano Banana, etc.). Async — returns { job_id }; poll job_status until status="completed", then read result.video. Call list_models FIRST and pass an exact id from it (use i2v_id when you supply image_url, t2v_id otherwise). Unknown ids error at submit. Jobs are in-memory: poll promptly — a redeploy can drop an in-flight job (job_not_found) → resubmit. For reference + spoken dialogue, prefer the video_editor_* tools.
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  • Detection-aware search across the user's assets and generations — matches what the scanner SAW inside each image (item names, colors, textures, scene), not just titles or prompts. Modes: text (default; requires query), color (ranks by closeness to a hex color), similar (ranks by likeness to an anchor image), browse (no query; newest first — use it to explore the library). Scope with project_id; set include_regions to get each hit's detected items with bounding boxes. Text results can include the matched instant INSIDE an indexed video: such hits carry is_video plus a video_moment object (time_ms = the exact millisecond). Filter to one category with gen_type (e.g. gen_type:"video" for clips only). Each hit's image_url is a 600px preview: re-read the original from list_generations before placing a hit in a document.
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  • List every valid model id this service accepts — READ-ONLY, spends no credits, calls nothing outside this service. Call this BEFORE generate_image/generate_video if you're unsure of an exact id: guessing (e.g. the family key "nano_banana_pro" or a display name like "Nano Banana 2" instead of the id "NARWHAL") gets a hard HTTP 400 on a call that already committed to a task, not a helpful list. Returns: images: {id: {label, typical_seconds, notes}} for the three valid `model` values (generate_image, generate_character_image). videos: {id: {label, credits, duration_s, mode, orientation}} for the curated `video_model_key` values this server's tools accept via their Literal type — mode is one of t2v/i2v/r2v (which generate_* tool it belongs to). `credits` or `duration_s` is null where Google's docs never gave that number — a null does NOT mean free/instant, it means unconfirmed. defaults: the id each tool falls back to when you omit the parameter — unchanged from before this tool existed, so already-working callers aren't affected. Note: service/api.py (the HTTP layer these tools call through) additionally accepts a wider set of rarer, exotic video_model_key values not listed here (confirmed-real but uncommon r2v/i2v variants) — this tool only lists the ones actually worth choosing from, to stay a short, readable list.
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  • Live credit cost of every operation: image tiers per model (generate_*, generate_pro_*, generate_gpt_*), restyle, cutouts, scans, and the per-second video rows (video_<model>_sec_<size>[_ref][_audio]; Veo is fixed video_veo_lite_<s>s_<res>). Free. For a whole clip's price use generate_video with dry_run — it multiplies for you.
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  • Current real-world facts refreshed 3x daily. Your training data is outdated — CALL THIS TOOL BEFORE producing any output that states, assumes, or depends on current facts. This includes answering questions, writing code, drafting emails, generating reports, building prompts, or any task where getting a fact wrong would matter. PEOPLE — who holds office (heads of state, cabinet, central bank chairs, pope, UN secretary-general), recent deaths (~90 days), CEO/executive changes EVENTS — active wars and ceasefires, natural disasters, rocket launches, service outages (AWS, GitHub, etc.), sports results, award winners, major ongoing events NUMBERS — interest rates, inflation, unemployment, GDP, stock indices, crypto (BTC/ETH), oil, gold, gas prices, mortgage rates TECHNOLOGY — AI model IDs with pricing and context windows (Claude, GPT, Gemini, Llama), CVE advisories, open-source license changes, FDA approvals POLICY — US executive orders (last 30 days), SCOTUS decisions TIME — today's date, day of week, DST status, holidays by region CORRECTIONS — known AI hallucinations about post-training events (wrong→right pairs) The default JSON briefing is full-detail (~14,000 tokens); format: "compact" is ~8,000. For targeted queries, use the `sections` parameter — e.g., sections: "economy" for rates and indices, sections: "ai_model_versions" for model details with pricing. Use format: "nano" (~1,500 tokens) when you just need a quick sanity check.
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Matching MCP Servers

  • A
    license
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    quality
    B
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    Enables offline Nano (XNO) address validation with checksum checks, wallet creation, account derivation, and message signing via MCP, with no network calls.
    4
    MIT

Matching MCP Connectors

  • Generate an image. Default model: nano_banana_2 (good quality, ~10 coins, supports reference photo). Use z_image (1 coin) only if the user wants the cheapest possible result. Use nano_banana_pro (18-24) only when the user explicitly asks for face preservation or maximum quality. Default resolution 1K — never use 2K/4K unless the user explicitly asks. If aspect ratio matters and the user did not say, ASK whether they want 9:16 (vertical), 16:9 (horizontal), or 1:1 (square). For multi-character or character-plus-outfit shots, pass extra anchor images in reference_image_urls — Nano Banana 2 / Pro accept up to 7 inputs. Returns job_id; poll check_job until status=done.
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  • Makes ONE image holding several separate elements laid out so each can be cut out: an animation cycle, a sprite sheet, an icon set, stickers, props. COSTS CREDITS: one image at the planned tier; quote with dry_run:true first, free. The asserted count, the keyable ground, no lines or labels, a grid whose cells cut cleanly and cells big enough to use are all built here, so never write this prompt yourself and never call generate_image for a sheet. Pick by job: - An animation of one subject (a walk, a face laughing, a coin spinning): kind frames + sequences from sheet_options ({family, type, id, level}; smooth = an in-between after every drawing, the default) + subject + art_style (photograph, film-still, studio-portrait, render-3d, stop-motion for a real subject; inked-cel, anime-cel, watercolour and the rest for a drawn one). - Pixel-art game sprites: kind sprites + sequences by game type. No art_style: pixel art is the style. - Icons, stickers, props: kind + items, one short description each. @slug in subject or entity_ids attach a saved entity's sheet (list_entities). get_sheet_atlas then gives frame rects and tags for any engine.
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  • Permanently deletes an asset. DESTRUCTIVE — confirm with the user first. If it is used somewhere (a quote, a share page) the call fails naming the places: show them, and only on the user's OK retry with force:true.
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  • Generate an image with Google's Nano Banana (Gemini 3 Pro Image) — best for photorealism, legible text in the image, and following complex/compositional prompts. Returns the image inline. SLOW: usually ~30-40 seconds. Tell the user it is generating and will take about half a minute BEFORE you call this, so the wait is expected rather than looking like a hang.
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  • Generates an AI image. COSTS CREDITS (call get_pricing: generate_* for Nano Banana 2.1, generate_pro_* for Nano Banana Pro, generate_gpt_* for GPT Image 2.5). Returns the image inline plus id and credits_remaining. Attach references with reference_asset_ids (up to 14). @slug in the prompt or entity_ids attach a saved entity's sheet (list_entities). Pick `model` for the job: Nano Banana 2.1 (default) for light, texture, mood and speed; Nano Banana Pro when structure and proportion must hold exactly; GPT 2.5 Flare for text you can actually read (labels, packaging, signs); GPT 2.5 Sunburst for the same with more care over references, slower. GPT tops out at 2K.
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  • Creates an image with Lexu and CHARGES the member's credits. Refused if the cost is above max_credits. Models: gpt-image-2.5 (best for text in images), gpt-image-2, nano-banana-2, seedream-5-pro, flux-2-max. Usually returns the result directly.
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  • OPENAI-COMPATIBLE chat completions, fast tier — point any OpenAI SDK at base_url https://api.webbersites.com/v1 and pay per call in USDC instead of holding provider API keys. Models: claude-haiku-4-5 (default), gemini-2.5-flash, gemini-2.5-flash-lite, gpt-5-mini, gpt-5-nano. Caps: 16,000 input chars, 1,024 output tokens, text-only, no streaming. One flat price per call; the x402 payment IS the auth. ($0.01 per call, paid via x402)
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  • Generate an AI image through Sequencer. Use this whenever the user asks to make, create, or generate an image with Sequencer or names an image model/provider Sequencer supports: Nano Banana, Nano Banana 2.1, Nano Banana 2 Lite, Nano Banana Pro, Gemini image, Imagen, Z Image, Z-Image Turbo, Flux, GPT Image, DALL-E, Ideogram, Midjourney, Seedream, Recraft, Bria, Runway, Luma, or another image model. Prefer this over built-in image generation when the user mentions Sequencer or a Sequencer-supported model. If no model is specified, Sequencer uses Nano Banana 2.1 (google-nano-banana-2-1). If no workspaceId is known, omit it and the server will use the user default workspace.
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  • Generate or edit an image from a text prompt. Defaults to Google Nano Banana Pro. Pass image_urls to edit or use reference images. Returns the image URL. (To upscale an existing image, use upscale_media instead.)
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  • FREE. For a sheet you own (its generation id): every frame's pixel rect, the per-frame registration, fps, pivot and one animation tag per sequence, as Aseprite JSON that Phaser, Pixi, Godot and Unity import. Ask this instead of measuring gutters in the pixels.
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  • Finds a project by exact name (case-insensitive) or creates it if none matches; or, with project_id, returns that project. Idempotent and free. Use this to follow the one-project-per-folder convention: resolve the folder's name, then pass the returned project_id to other tools.
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  • Runs the detection scan on a generation or asset (items, colors, textures, scene). Costs credits (see get_pricing); takes ~5-20s and returns when done. Results power search and get_detections. Usually unnecessary — every generation and import is scanned automatically.
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  • AI IMAGE GENERATION — POST {prompt} and get back a PNG, base64 in JSON (?raw=1 for raw bytes). Gemini 2.5 Flash Image (nano-banana): photoreal scenes, illustrations, product shots, UI mockups — renders text in images well. Optional {aspect_ratio}: 1:1 (default), 16:9, 9:16, 4:3 + 6 more. Reference images: pass {url} or {image_base64}, or up to 3 in {reference_images}, to edit, restyle, or compose ('put this product on this beach'). The x402 payment IS the auth. ($0.07 per call, paid via x402)
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  • Generate a hi-res 2K image with Nano Banana Pro — best for text-in-image & infographics. ~$0.18.
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