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

Extract text and Markdown from local PDFs and images. Uses native PDF text first and Apple Vision OCR on macOS. No OCR API key required.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

MCP server for uploading local images to Sanity CMS. Enables AI assistants to upload files from your filesystem directly into Sanity as image assets.

Enables AI agents to process files locally — OCR images, extract text from PDFs and DOCX, and describe images using local vision models, all without sending data to external services.

Enables writing text content to Markdown files with folder organization and overwrite control, and listing recent Markdown files.

Enables coding agents to extract verbatim, intent-relevant spans from large low-density files like logs, CSV, JSON, and HTML, verified against the original file to reduce context usage.

Rust-powered PDF toolkit over MCP: create, read, and analyze PDFs; extract text and entities for RAG; convert to Markdown; split/merge/rotate/reorder pages; manage form fields and annotations; encrypt documents. Runs locally via uvx oxidize-mcp.

MCP server for translating PDFs using pdf2zh-next, preserving document context by extracting all text segments for LLM translation at once.

Enables local conversion of PDFs to Markdown, with automatic OCR fallback for scanned pages, image extraction, and page-by-page structure preservation.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

Enables vision LLMs to read PDFs by automatically detecting text corruption and switching between text extraction and image rendering modes, while preserving reading order and filtering unnecessary images to prevent token overflow.

Enables an AI assistant to reliably read and chunk PDF/text documents, validate extracted JSON against a schema with full error paths, and save structured output—all confined to a single allowed directory.

Enables AI agents to read and extract text, tables, and image content from files (PDF, DOCX, PPTX, SVG, PNG) within a folder, providing structured data for interpretation by the calling model.

Enables AI assistants to read local documents by converting PDFs, Office files, images, and audio to Markdown on-device, without uploading them.

stdio server to read markdown with images or index markdown headings from a file, folder or URL

Enables AI agents to inspect PDFs, merge or extract pages, and clean text entirely offline through the Model Context Protocol, with no uploads, API keys, or network calls.

Provides structured, read-only access to DXF drawings, enabling listing of drawings, layer inventories, bill-of-materials extraction from block attributes, text search, and drafting-standards checks.

Enables AI agents to list, read and download the files attached to Gmail messages, extracting text from PDFs, Word, Excel, PowerPoint and plain-text files straight into context or saving them to disk. It runs locally with read-only Gmail access, so attachments can be summarised, checked or analysed without leaving the chat.

Enables AI agents to efficiently process large local and online PDFs through selective extraction of text, images, and metadata. It provides tools for content search and document outline navigation to optimize context window usage.