"Tools or platforms for generating basic images from text prompts" matching MCP tools:

• tool_search

  Power Automate MCP Server by Flow Studio

  PREFER THIS over guessing tool names when picking from this server. Searches Flow Studio MCP tools by keyword, skill bundle, or explicit selector and returns full JSON schemas for matched tools so they can be called immediately. Call this whenever the user request maps to functionality you are not 100% sure about, OR when you want to load a whole skill bundle (build-flow, debug-flow, monitor-flow, discover, governance) at once. Query forms: (1) "skill:<name>" — fetch the full bundle (use list_skills first to see options); (2) "select:name1,name2" — fetch exact tools by name; (3) free-text keywords like "cancel run" or "trigger url" — ranked match against tool name + description. Non-billable.

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• upload_file

  BorealHost

  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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• fetch_document

  openregistry

  Primary tool for reading a filing's content. Pass a `document_id` from `list_filings` / `get_financials`. MANDATORY for any substantive answer - filing metadata (dates, form codes, descriptions) alone doesn't answer the user; the numbers and text live inside the document. ── RESPONSE SHAPES ── • `kind='embedded'` (PDF up to ~20 MB; structured text up to `max_bytes`): returns `bytes_base64` with the full document, `source_url_official` (evergreen registry URL for citation, auto-resolved), and `source_url_direct` (short-TTL signed proxy URL). For PDFs the host converts bytes into a document content block - you read it natively including scans. • `kind='resource_link'` (document exceeds `max_bytes`): NO `bytes_base64`. Returns `reason`, `next_steps`, the two source URLs, plus `index_preview` for PDFs (`{page_count, text_layer, outline_present, index_status}`). Use the navigation tools below. ── WORKFLOW FOR kind='resource_link' ── 1. Read `index_preview.text_layer`. Values: `full` (every page has real text), `partial` (mixed), `none` (scanned / image-only), `oversized_skipped` (indexing skipped), `encrypted` / `failed`. 2. If `full` / `partial`: call `get_document_navigation` (outline + previews + landmarks) and/or `search_document` to locate pages. If `none` / `oversized_skipped`: skip search. 3. Call `fetch_document_pages(pages='N-M', format='pdf'|'text'|'png')` to get actual content. Prefer `pdf` for citations, `text` for skim, `png` for scanned or oversized. ── CRITICAL RULES ── • **Navigation-aids-only**: previews, snippets, landmark matches, and outline titles returned by the navigation tools are for LOCATING pages. NEVER cite them as source material - quote only from `fetch_document_pages` output or this tool's inline bytes. • **No fallback to memory**: if this tool fails (rate limit, 5xx, disconnect), do NOT fill in names / numbers / dates from training data. Tell the user what failed and offer retry or `source_url_official`. • Don't reflexively retry with a larger `max_bytes` - for big PDFs the bytes are unreadable to you anyway. Use the navigation tools instead. `source_url_official` is auto-resolved from a session-side cache populated by the most recent `list_filings` call. The optional `company_id` / `transaction_id` / `filing_type` / `filing_description` inputs are OVERRIDES for the rare case where `document_id` didn't come through `list_filings`. Per-country document availability, format, and pricing - call `list_jurisdictions({jurisdiction:"<code>"})`.

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• erase

  cnvs.app

  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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• get_project_testimonials

  Kolmo Construction

  Get customer testimonials tied to a specific project (by slug or keyword) from the testimonials table. Returns star rating, customer name, project name, and quote text. Use to source social proof or case-study quotes for a particular job. For unfiltered reviews, use list_reviews.

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• extract_document

  Sats4AI - Bitcoin-Powered AI Tools

  Extract text from PDFs and images as clean Markdown. Uses Mistral OCR — handles complex layouts, tables, handwriting, multi-column documents, and mathematical notation. Preserves document hierarchy in structured Markdown. 10 sats/page. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='extract_document' and quantity=pageCount for multi-page PDFs.

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• ceevee_get_version

  CareerProof MCP

  Get detailed CV version including structured content, sections, word count, and audience profile. cv_version_id from ceevee_upload_cv or ceevee_list_versions. Use to inspect CV content before running analysis tools. Free.

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• delete_tags

  Peec AI MCP Server

  Soft-delete up to 50 tags in a project. Removes tag associations from prompts. Returns per-item results (deleted / skipped). This is destructive — always confirm with the user before calling.

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• t54_list_operations

  Agentic Swarm Marketplace (T54 x402 MCP)

  Returns operationIds, HTTP methods, paths, and query parameter names from the bundled OpenAPI spec (no network). Use before t54_x402_request or per-SKU tools.

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• search_recalls

  DeepRecall - Product Safety Intelligence

  Search for recalled products similar to your query. This tool searches DeepRecall's global product safety database using AI-powered multimodal matching. Provide a text description and/or product images to find similar recalled products. Use Cases: - Pre-purchase safety checks: Before buying, verify if similar products were recalled - Supplier vetting: Check if a supplier's products have safety issues - Marketplace compliance: Verify products against recall databases - Consumer protection: Identify potentially hazardous products Data Sources: - us_cpsc: US Consumer Product Safety Commission - us_fda: US Food and Drug Administration - safety_gate: EU Safety Gate (Europe) - uk_opss: UK Office for Product Safety & Standards - canada_recalls: Health Canada Recalls - oecd: OECD GlobalRecalls portal - rappel_conso: French Consumer Recalls - accc_recalls: Australian Competition and Consumer Commission Cost: 1 API credit per search Args: content_description: Text description of the product (e.g., "children's toy with small parts") image_urls: List of product image URLs for visual matching (1-10 images) filter_by_data_sources: Limit search to specific agencies (optional) top_k: Number of results (1-100, default: 10) model_name: Fusion model - fuse_max (recommended), fuse_flex, or fuse input_weights: Weights for [text, images], must sum to 1.0 api_key: Your DeepRecall API key (optional if provided via X-API-Key header) Returns: Search results with matched recalls, scores, and product details Example: search_recalls( content_description="baby crib with drop-side rails", top_k=5 )

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• get_board

  cnvs.app

  Full structured JSON state of a board: texts (id, x, y, content, color, width, postit, author), strokes (id, points, color, author), images (id, x, y, width, height, dataUrl, thumbDataUrl, author; heavy base64 >8 kB elided to dataUrl:null, tiny images inlined). Use this for EXACT ids/coordinates/content (needed for `move`, `erase`, editing a text by id). For visual layout (where is empty space? what overlaps?) call `get_preview` instead — it's much cheaper for spatial reasoning than a huge JSON dump.

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• move

  cnvs.app

  Reposition an existing item to a new (x, y) without retyping its content. Works for every item kind: `text` and `link` set the top-left to (x, y); `line` translates every point so the stroke's bounding box top-left lands at (x, y); `image` sets the top-left like text. `kind` defaults to `text` for backward compat with older callers. Find the id + kind via `get_board`. Prefer `move` over re-creating an item when only the location changes — it preserves the id, content, author and avoids a round-trip of base64 bytes for images.

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• bgg-details

  kkjdaniel-bgg-mcp

  Get detailed information about board games on BoardGameGeek (BGG) including description, mechanics, categories, player count, playtime, complexity, and ratings. Use this tool to deep dive into games found via other tools (e.g. after getting collection results or search results that only return basic info). Use 'name' for a single game lookup by name, 'id' for a single game lookup by BGG ID, or 'ids' to fetch multiple games at once (up to 20). Only provide one of these parameters.

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• list_starter_prompts

  Vocab Voyage

  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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• upscale_image

  Sats4AI - Bitcoin-Powered AI Tools

  Upscale images 2x or 4x with neural super-resolution. Uses Real-ESRGAN (ICCV 2021, PSNR 32.73dB on Set5 4x, 100M+ production runs). Recovers real detail from low-resolution images — not interpolation. Optional face enhancement. Stable endpoint — model upgrades automatically as SOTA evolves. 5 sats per image, pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='upscale_image'.

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• parliament_search_hansard

  UK Legal Research

  Search Hansard for parliamentary debates, questions, and speeches. Returns contributions from MPs and Lords including date, party, debate title, and text (capped at 3000 chars per contribution). Useful for understanding legislative intent or political context.

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• upload_asset

  mcp

  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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• files_read

  DialogBrain

  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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• analyze_image

  sheetsdata-mcp

  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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• download_attachment

  myagentinbox

  Download an email attachment. Returns images as base64, text files inline, and binary files as download URLs.

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