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685,578 tools. Updated 2026-10-22 15:05

"How to extract text from images" matching MCP tools:

  • Generate game-art images from a text prompt alone, selecting an image_type (e.g. sprite) and optionally art_style, perspective, and aspect_ratio. The job result is an array of image results, each with a url; request n (1-8) to control how many variations come back. Because it generates purely from text it takes no source image, so there is no upload size limit to trip. Credits are held when the job is accepted and refunded if it fails or is cancelled; the charge scales with the number of images produced. Use createImage to make new images from scratch; use generateWithStyle to match a reference image's art style, editImage to modify an existing image, and removeBackground to cut out a subject. Pass an optional request_id to tag the results so you can retrieve them later via listGenerations (type image). Async generation job: returns `{id, status}` - poll `getApiJob` (job and credit contract: see the server instructions). Credits: This endpoint consumes 0.5 credits per result.
    ConnectorNo auth
  • USE THIS to extract structured {country, postcode, city, state} from a free-text UK or US address — when onboarding a user, running a KYC/fraud check, or storing an address — instead of splitting the string yourself. Returns a confidence flag.
    ConnectorNo auth
  • Use this when the subject is images — alt text, image descriptions, 'do our images have alt text' — across the whole site, from the scan already on record. For one page checked right now, including one no scan has covered, use check_page_alt_text. Alt-text problems found on a website's most recent scan: images with missing, filename-like, vague or inaccurate alt text, each with the element selector, the current value, why it was flagged, and a suggested replacement. Scoped to the current scan, not the whole history. Each finding also carries "markupHint": an <img> tag rebuilt from the stored image URL and alt value, so you have something greppable — the selector describes the rendered DOM and appears in no source file. It is a reconstruction, not the markup that was scanned, so treat the src path and the alt value as search strings rather than diffing it against your source. How the counts relate: "rawFindings" is every row on record for the scan, "distinctImages" is how many source images those rows collapse to once per-page repeats and cache-variant URLs of one asset are merged, and "returned" is how many of those are in this response — returned <= distinctImages <= rawFindings, and the work is one alt decision per distinct image. A finding's "affectedImages" is a different kind of number and the one you must not sum: it counts images on that page sharing the finding's template, and every finding sampled from one template repeats it, so three findings reading 7 are one group of seven. "templateGroup" says which findings share a group, and "imagesInAffectedTemplates" is that roll-up already done once per group — quote it as the image total rather than adding anything up. "suggestedAlt" is written from the image alone, by a pass that never saw the page around it: if the image is decorative, or an adjacent link or caption already names the destination, alt="" is the correct fix and not the description offered — validate_fix on image-alt confirms alt="" as resolved. Every suggestion carries that as "suggestionCaveat"; the judge_alt_text prompt is the long version. Read-only — it does not change any alt text.
    ConnectorAPI key
  • Extract page text and heuristic tables from a base64-encoded PDF for downstream reasoning. Call for general PDF text hops — receipt/invoice field extraction belongs to parse.receipt / parse.invoice. Inputs: file_base64 (or pdf/base64 aliases); optional options.includeTables / maxPages. Decoded size ≤ 10 MiB. Outputs pages[].text and optional tables. Paid (~10 credits / $0.10) via prepaid key or x402.
    ConnectorNo auth
  • Generate images from text prompts. Returns a hosted URL of the PNG and the same image as base64 (b64_json), with the aspect ratio and size used. Use to create a new picture from a description. To cut the background out of an existing image use bg-remove; to capture a web page use screenshot. Cost: 3 credits, charged only when a call succeeds.
    ConnectorNo auth
  • Reads a note, an app file, an app's data.json or a file, with line numbers (cat -n). Long text is read in parts: offset is the first line, limit how many (default 2000). A folder reads as its listing. Files: text files (TXT, CSV, JSON, code) as text you can edit; PDFs, Word, Excel and PowerPoint as their text; pictures as images. raw: true returns the file itself (base64, up to 10 MB).
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  • Extract text from PNG, JPEG, TIFF, WebP, BMP and GIF images with OCR in 27 languages.

  • Word .docx to text and tables. x402 $0.005 USDC, Base. As is, no warranty.

  • 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.
    Connector
    Destructive
    No auth
  • Extract clean text (per page + full) and metadata from any public PDF URL up to 25 MB / 200 pages. Pay per call with USDC or USDT on Base via x402. 3 free calls per wallet.
    ConnectorNo auth
  • Extract title, meta description, ~3k chars plain text and outbound links from a URL (local fetch). Use when you need readable page text cheaply. Not for clean markdown of JS-heavy pages (use web-extract). Returns a free sample plus the paid URL and pay steps (no charge here); the full result costs $0.02 Base USDC via x402.
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  • Extract clean readable content from up to 20 URLs — returns text, title, author, published date. Eliminates scraping. Perfect for feeding web pages into agent context windows (Tavily)
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  • Full detail for one product: description (up to 600 chars), materials, dimensions, weight, images, variants, artist and text rights. Read-only — does not reserve or buy. Use the product id from nodajimarket_search_products.
    ConnectorNo auth
  • OCR an image URL with local Tesseract: text, word count, confidence. Use when you need text from a screenshot or scanned image. Not for web pages (use url-extract). Returns a free sample plus the paid URL and pay steps (no charge here); the full result costs $0.01 Base USDC via x402.
    ConnectorNo auth
  • Extract structured data from URLs or content. Returns the extracted data as JSON (shaped by your schema when you pass one), with the source URL and whether long content was truncated. Use to turn a page or a text into structured fields. For a page's full text use scrape; for invoices and receipts use invoice-parse. Pass url or content; extraction_prompt says what to extract, and schema fixes the shape of the JSON you get back. Cost: 3 credits, charged only when a call succeeds.
    ConnectorNo auth
  • Convert documents, web pages, spreadsheets and images between formats. Returns a download URL of the converted file with its name, size and formats. Use to change a file's format, for example Word to PDF or PDF to Markdown. To extract specific fields use documents; to read a web page's text use scrape. Cost: 2 credits, charged only when a call succeeds.
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  • Extract structured JSON from a web page (by URL) or raw HTML: title, byline, excerpt, siteName, publishedTime, language, plain text, links, images, and meta tags. Paid tool: $0.005 per call via x402 (USDC on Base).
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  • Extract the text of a PDF and convert it to clean markdown. Detects headings by font size and preserves lists and paragraphs. Input: a text-based PDF via file_url or file_base64. For scanned PDFs use ocr_image on page images instead.
    ConnectorNo auth
  • 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.)
    Connector
    Destructive
    No auth
  • Extract image/media asset URLs from indexed markdown text. Use only when the user asks for product images, media files, visual assets, screenshots, WordPress uploads, or image evidence. For textual questions about extracted page content, use search_content instead. Returns asset URLs plus the real page URL where each asset appeared.
    ConnectorNo auth
  • Extract plain text from a PDF or image (base64-encoded). Use when you need raw text for downstream AI analysis (summarization, claim checking, structured extraction). For documents at a public URL, use extract_url instead (no base64 encoding needed). Returns: { pages: number, text: string } Example prompts: - "Extract the text from this scanned contract so I can search it." - "Give me the raw text from this PDF document." - "OCR this image and return the text content."
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  • Extract plain text from a PDF or image (base64-encoded). Use when you need raw text for downstream AI analysis (summarization, claim checking, structured extraction). For documents at a public URL, use extract_url instead (no base64 encoding needed). Returns: { pages: number, text: string } Example prompts: - "Extract the text from this scanned contract so I can search it." - "Give me the raw text from this PDF document." - "OCR this image and return the text content."
    ConnectorNo auth
  • Fetch a single note's full text and metadata by its id. If the note has images attached (up to 3, for example a screenshot of a post the user saved), they are returned as image content after the text so you can see them. Note results from the other tools list these under `images` with short-lived signed URLs; call this tool to view them.
    ConnectorOAuth