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127,227 tools. Last updated 2026-05-05 10:29

"An MCP for generating images" matching MCP tools:

  • 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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  • [READ] Search the Layer 3 curated directory of MCP servers and agent-work tools. The directory has 30 entries across three vetting tiers — `first-party` (operated by the swarm.tips DAO), `vetted` (third-party, we've used + verified), `discovered` (cataloged from public sources, not yet exercised). Filter by `query` (substring vs name/description/tags), `category` (substring), and `tier`. Results sort first-party → vetted → discovered. The same directory powers swarm.tips/discover; this tool exposes it programmatically. Use this when an agent needs to find an MCP server for a capability (DeFi, search, browser automation, etc.) instead of an opportunity (which `discover_opportunities` covers).
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  • Export a generated image asset by session and asset ID. Returns the image inline as base64 along with metadata (format, dimensions, size). When running locally (stdio transport), you can optionally provide a destinationPath to save the image to disk. USAGE: After generating an image with generateImage, use the sessionId and assetId to export: exportImageAsset(sessionId="...", assetId="...") To save to disk (local/stdio only): exportImageAsset(sessionId="...", assetId="...", destinationPath="/Users/me/project/images/logo.png")
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  • Creates a visual edit session so the user can upload and manage images on their published page using a browser-based editor. Returns an edit URL to share with the user. When creating pages with images, use data-wpe-slot placeholder images instead of base64 — then create an edit session so the user can upload real images.
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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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  • Submit an extension request for existing delegated resources on TronSave via authenticated REST `POST /v2/extend-request`. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; the server forwards the API key cached in session to TronSave internal REST endpoints. Side effect: creates an extension order and may commit TRX from the internal account. `extendData` must follow the REST contract (see schema on each row). Populate it from TronSave outside this MCP—for example the authenticated `POST /v2/get-extendable-delegates` response field `extendData`, or another TronSave client. Do not copy rows blindly from `tronsave_list_extendable_delegates` (GraphQL); that payload shape differs and is for market discovery only.
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Matching MCP Servers

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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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  • Upload an asset (image, font, PDF, etc). Provide exactly one of: content (base64), content_text (plain text for JS/CSS/JSON/SVG — preferred, saves tokens), or source_url (public HTTPS URL for images). Set overwrite: true to replace an existing asset.
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  • Save a file (PDF, PPTX, DOCX, etc.) to a client's record in the broker's CRM. Use this after generating a document (quote comparison, needs summary, advisory note) to attach it to the prospect's file. The client must already exist as a lead (use save_lead first). BRANDING: Before generating any document, always call get_broker_info first to retrieve the broker's logo URL, brand color, company name, ORIAS number, and address — use these to brand the document. The file content must be base64-encoded.
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  • Read the contents of an attached file directly. Use this when the user asks 'what is in this file?' or 'read this document'. Works for text files (.txt, .md, .json, code files, etc.) and PDFs (returns OCR-extracted text after files.ingest). For images, use files.get_base64.
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  • Lists Vocab Voyage's MCP starter prompts (also exposed via the standard MCP prompts/list endpoint). Useful for hosts that don't yet support prompts/list.
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  • Get the full data bundle for an artwork — everything Raisonnai knows about a single work. Includes: core identity, provenance chain, exhibition history, bibliography, media set, condition history, trust metadata (completeness + trust scores), attestation log, and cryptographic credentials. Use this when an agent needs the complete picture for reasoning about an artwork — verification, purchase evaluation, provenance assessment, or portfolio analysis. For lightweight queries (just title, medium, images), use get_work instead. Resolve the work by either workId (UUID) or uwi (e.g. "RAI-2026-00417"). To find the workId, use search_natural_language — never ask the user for it.
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  • Get an upload URL to upload a single image to a project. Returns a pre-built upload URL and instructions. The caller must perform the actual upload using curl since the MCP server cannot access local files. This endpoint uploads images only. To add annotations, call annotations_save with the image ID from the upload response. For bulk uploads with annotations, use images_prepare_upload_zip.
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  • List all slide presentations created in the current MCP session. Returns URLs, themes, and timestamps for each presentation you've created.
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  • Run hosted inference on an image using a trained model. Returns JSON predictions only. For visualized/annotated images, use workflow_specs_run with a visualization block instead.
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  • Get report status and metadata. Returns status (pending/generating/completed/failed), title, type, and summary. When status='completed', download the PDF with atlas_download_report(report_id). report_id from atlas_start_report response or atlas_list_reports. Free.
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  • Bridge an A2A (Agent-to-Agent Protocol) task to an MCP server. Receives an A2A task, identifies the best matching MCP tool on the target server, executes it, and returns the result wrapped in A2A response format. Enables A2A agents to use any MCP server transparently. Extracts the intent from the A2A task, maps it to an MCP tool, calls the tool, and wraps the result in A2A response format. Use this to let A2A agents interact with any MCP server. Requires authentication.
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