Read non-Markdown files in Obsidian vaults: images, PDFs, canvases, and text with type-appropriate output — viewable images, structured PDF text or page images, canvas outlines, and verbatim text.
MIT
404,457 tools. Last updated 2026-08-06 21:17
"Tools for Reading Text from PDFs and Images" matching MCP tools:
- Download a file from Google Drive by providing its file ID. Returns binary content for PDFs, images, and other files.MIT
- View a file attachment from a Todoist comment. Pass the fileUrl from the comment's fileAttachment field to display images, text, or binary files like PDFs.MIT
- Extract raw text from base64-encoded PDFs or images for AI analysis such as summarization, claim checking, or structured extraction. Returns page count and text content.MIT
- Generate images from text prompts, optionally with reference images for editing. Returns finished image URLs and previews.MIT
- Add text annotations, images, and fill form fields in PDF files. Modify scanned PDFs with links, shapes, and external content.MIT
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- Retrieve your past render results including images, PDFs, and screenshots. Filter by template or batch, and paginate to navigate through results.Apache 2.0
- Create images from text descriptions. Choose size, style, model, and number of images to generate.MIT
- Retrieve a curated list of featured AI workflows for generating images, text, and other content.MIT
- Convert PDFs and scanned images into JSON representation, preserving text, fonts, images, vectors, and formatting.MIT
- Create images from text prompts with customizable styles and variations.Apache 2.0
- Extract structured content and layout from PDFs, images, and Office files. Supports output formats like HTML, text, and markdown.MIT
- Extract structured content from PDFs, images, and Office files while preserving original formatting and layout using Upstage AI's document digitization API.MIT
- Extract text from PDFs with Y-coordinate reading order. Handle multi-column layouts and compact whitespace for Japanese forms to reduce token consumption.MIT
- Extract text from USPTO petition documents using hybrid extraction: free PyPDF2 for text-based PDFs, Mistral OCR for scanned documents. Analyze legal arguments, issues, and patterns in petition decisions.MIT
- Extract text from local images and PDFs with Apple Vision OCR, returning plain text or structured blocks with bounding boxes. Works offline on macOS.MIT
- Extract text, faces, barcodes, and rectangles from images and PDFs in reading order for document reconstruction. Works fully offline with no API keys.MIT
- Converts PDF to reading-order Markdown for LLM consumption. Reconstructs up to 2 content columns, infers headings from font size, detects lists; tables rendered as plain text.MIT
- Compare two PDFs page by page to detect text differences. Reports identical pages and trimmed diffs for same-layout documents.MIT
- Read the full content of a Bear note by ID or title. Includes text extracted from images and PDFs with clear labeling.Apache 2.0