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289,834 tools. Last updated 2026-07-12 06:59

"A server for generating images" matching MCP tools:

  • Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search first to find valid names.
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  • Display the user's images inline — one or many. Users speak plainly and will NOT know asset ids; never ask for one, resolve it yourself. For "show me" or "show me my last image" call with NO arguments (shows the most recent image). For "show me my last 4 images / my last 10 pictures" pass count=N (returns a clean grid, up to 12). For a specific known image pass assetId. Renders a branded SwitchApp media card with a Download action per result; do not just print URLs. (Videos are not shown here — use list_my_videos and return the newest finished video's view_url, which plays.)
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  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
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  • Make an image tahta-grade for a deck's variant (editor+): crop to 16:9, apply a scheme-aware duotone (palette-lock), grain, and an optional contrast scrim. Upload the source with upload_attachment first, then pass its attachment_id; the treated JPEG is saved as a new attachment and returned with a ready-to-place ![](…) snippet for a bg:/image: slot. This is the tahta-imagine treat step — a FALLBACK for off-palette or reused images; prefer rich on-palette images raw, and never duotone (mode=duotone) a real-colour focal subject — use mode=none for those. See the imagery capability module (deck_authoring_guide module="imagery").
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  • 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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  • Order a VPS. `product` = plan slug from list_plans; `os_id` = an OS id from that plan's images. Optional `hostname` and `ssh_key` (public key — strongly recommended so you get key-based root login). Branching on the response: • `paid_from_balance: true` → the prepaid balance covered it; the server is provisioning. Poll `get_vps_status` until status is `active` and the VM is reachable. • `paid_from_balance: false` → balance was insufficient; an unpaid `invoice` is returned. Call `pay_invoice` with `invoice.id` to get a crypto `checkout_url`, OR `topup_balance` then re-order.
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Matching MCP Servers

Matching MCP Connectors

  • 斯特丹STERDAN天猫旗舰店产品咨询MCP Server。洛阳30年源头工厂,高端钢制办公家具,1374个SKU,涵盖保密柜、更衣柜、公寓床、货架、快递柜。BIFMA认证,出口35+国家。8个工具:产品目录查询、场景推荐、认证资质、采购政策、维护指南等。

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  • Edit an existing image and place the result directly on a user's Avocado AI flow (the Flows Director). This is the flow-native edit: use it (NOT the plain edit_image) for ANY edit inside a flow, so the result lands in the user's Director Library. This MODIFIES ONE SPECIFIC existing image (file_id/image_url is required) — it does not generate new frames from a prompt. To generate a NEW image guided by one or more reference images (e.g. a storyboard beat that must keep the same cast/location consistent), use generate_image_to_flow with reference_image_urls instead. Drops a 'Generating...' tile immediately, then swaps in the edited image when ready (10-60s). REQUIRED: exactly one of file_id OR image_url (HTTPS). For chat-attached images call prepare_image_upload first, then pass the returned file_id. Models: 'nano-banana-2' (fast, default, 1 credit), 'nano-banana-2-lite' (fastest/cheapest, single-image touch-ups, 1 credit), and 'gpt-image-2' (higher quality, 1-4 credits by quality). To regenerate/retouch an EXISTING tile in place (same tile stays 'the' cast/location/beat reference — nothing downstream breaks) instead of creating a duplicate, pass replace_node_id (get it from a prior generate_image_to_flow/edit_image_to_flow response's nodeIds, or from list_flow_assets); typically image_url would then be that same tile's own current url.
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  • Render every actionable segment asset (images, video clips, overlays) across the project, in dependency order. THE most expensive call in the pipeline: ALWAYS dry_run=true first, show your user the estimate next to get_credit_balance, and wait for a fresh yes before the real run — prior blanket permission ("do the whole thing") does not cover this spend. Pass segment_numbers to render only a subset — e.g. segments 1-18 for the opening minute before committing to the full video. Safe to re-run: completed and currently-generating assets are skipped, so a second call only picks up new/failed work. Async — one job per asset; await_jobs until all complete.
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  • Analyze an image from a component's datasheet using vision AI. Use this when read_datasheet returns a section containing images and you need to extract data from a graph, package drawing, pin diagram, or circuit schematic. Pass the image_key from the read_datasheet response (the storage path in the image URL). Optionally pass a specific question to focus the analysis. IMPORTANT: For precise numeric values (electrical specs, max ratings), prefer read_datasheet text tables first — they are more reliable than vision-extracted graph data. Use analyze_image for visual information not available in text: package dimensions from drawings, pin assignments from diagrams, graph trends, and approximate values from characteristic curves. Examples: - analyze_image(part_number='IRFZ44N', image_key='images/abc123.png') -> classifies and describes the image - analyze_image(part_number='IRFZ44N', image_key='images/abc123.png', question='What is the drain current at Vgs=5V?')
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  • Validate a TypeScript intent definition without generating Swift. Runs the full Axint validation pipeline (134 diagnostic rules) and returns a JSON array of diagnostics: { severity: 'error'|'warning', code: 'AXnnn', line: number, column: number,... Use: use for TypeScript DSL diagnostics before Swift output; use swift.validate for existing Swift. Effects: read-only diagnostics; writes no files and uses no network.
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  • Get a fast suitability score (0-100) for a US property without generating a full report. Call this when the user wants a quick go/no-go assessment or an initial screening before committing to a full analysis. Returns a single score with confidence level and one-sentence rationale. Consumes a partial (0.25) analysis credit from your AcreLens account.
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  • 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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  • List all available VPS plans (catalog) with pricing, specs and the OS images each plan can boot. No authentication needed. Use this first to pick a `product` slug and an `os_id` for `order_vps`.
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  • List your campaigns with ID, name, status (draft/running/paused), description and lead counts. Use this to obtain campaign_id when adding leads, generating messages or approving drafts.
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  • List hosted images owned by the caller, with optional filters. ``source`` filters by upload origin: ``"upload"`` for directly uploaded images, ``"generated"`` for images created via the image generation tools. Omit to return all sources. ``visibility`` filters by access level: ``"public"`` or ``"private"``. Omit to return both. Pagination: pass ``next_cursor`` from a previous response as ``cursor`` to retrieve the next page. Returns ``{items: [...], next_cursor: str | null}``.
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  • Upload an image to PixelVault and get an instant CDN URL. Maps to POST /v1/images. Provide exactly one of `source_url` (a public http(s) URL the server fetches) or `data` (base64-encoded bytes); optional `folder` and `filename`. Max 5 MB; JPG/PNG/GIF/WebP/AVIF/SVG. Requires a PixelVault API key sent as a Bearer token in the Authorization header. The returned CDN URL supports on-the-fly transforms via query params — e.g. ?w=400&fit=cover (resize/crop), ?fmt=webp (format), ?segment=foreground (AI background removal → transparent PNG), effects like ?blur=30&saturation=0&rotate=90, and ?tile=<image_id.ext> (tile another of your images as a watermark). See https://pixelvault.dev/docs#transforms.
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  • Create a Revise document from a file at a public http(s) URL (.md, .markdown, .txt, .html, .htm, .docx; PDFs/images not yet supported). The server fetches the URL — file bytes are never passed inline. For a LOCAL file, use upload_document instead (it streams the file to the server). Returns the new document id and URL. Returns url (give it to your user — they view the document and create a free account to keep it, in one step) and edit_token (your Bearer token for future edits). The document is private and deleted after 7 days if unclaimed.
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  • Attach an image: target "product" or "banner" (ref required) or "logo" (venue logo, no ref). Source: EXACTLY ONE of sourceUrl (public https URL, server fetches it, ~15 MB cap) or base64 (inline bytes). Aspect rules: product and logo images must be SQUARE 1:1 — pass crop:"square" to have the server center-crop automatically; banner images must be 16:9 (no crop option). The server re-encodes/optimizes everything (WebP). preoptimized:true (product/banner only) uses the softer fast-lane rate bucket but REQUIRES the bytes to already be a target-size WebP — otherwise 400 PREOPTIMIZED_INVALID; when unsure, omit it.
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  • Delete a single item by id. `kind` MUST match the item type: 'text' for text nodes, 'line' for freehand strokes, 'image' for images — the wrong kind silently targets the wrong table and is a common mistake. Get the id + type from `get_board` (texts[], lines[], images[]). There is no bulk/erase-all tool: loop if you need to delete multiple items.
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