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

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.

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 Averra Extract — lets AI agents like Claude, Cursor, and ChatGPT convert any webpage into clean, LLM-ready Markdown.

Enables agents to perform full-text search and read Hermes Agent documentation offline from a local cache, without scraping the site.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI agents to capture clean web screenshots and extract main article content from any web page, with automatic removal of cookie banners, ads, and boilerplate.

Extract YouTube transcripts for AI agents, RAG pipelines, and LLM workflows. Supports any YouTube URL. Returns clean text or timestamped segments. No API keys required.

Verifiable document intelligence for AI agents. Extract text, tables, and structured data from PDFs and URLs. Summarize, answer questions, check claims, and translate — all with cited evidence. Store tamper-evident evidence bundles with cryptographic signatures and on-chain attestation via Base L2. Cross-document semantic search and Q&A across named collections. Pay per call with USDC

A Model Context Protocol server that connects GitHub code to Claude.ai. This server utilizes the Pera1 service to extract code from GitHub repositories and provide better context to Claude.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

Enables local-first hybrid knowledge retrieval from authorized Markdown and plain-text files, combining full-text and vector search with reranking and traceable source references via a single search tool.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

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

MCP server wrapping Docling to give text-only LLMs document vision via tools for converting PDFs, images, and Office files to Markdown, extracting tables, OCR, and RAG chunking.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

Enables Claude to scrape, crawl, extract data, and sync to vector databases using scrapedatshi's RAG pipeline, with support for multiple embedding and vector DB providers.

Web scraping, crawling, and structured data extraction for AI agents. 5 tools: scrape (clean markdown from any URL), crawl (entire sites), map (discover URLs), extract (structured JSON), and search. 833ms avg latency, single binary, self-hostable.

MCP server for Scrapiq, providing a tool to extract clean content from URLs. It returns title, content, links, and metadata in text, markdown, or JSON formats.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables RAG over messy PDFs — extract, chunk, embed, and search scanned, multi-column, and table-heavy documents.