TextIn OCR MCP

The TextIn OCR MCP server fills a critical gap for developers building AI assistants that need to ingest and understand information from a wide variety of document formats. By exposing powerful optical‑character‑recognition (OCR) and data extraction tools, it allows Claude or other LLMs to turn static files—images, PDFs, Word documents, and even spreadsheets—into structured text or Markdown. This capability removes the need for custom parsing pipelines and lets developers focus on higher‑level logic.

At its core, the server offers three main tools. recognition_text delivers plain‑text extraction from any supported file type, enabling downstream NLP tasks such as summarization or entity recognition. doc_to_markdown converts the same inputs into clean Markdown, preserving formatting while making content easily displayable in chat interfaces or web dashboards. general_information_extration goes further by automatically locating key fields (e.g., invoice totals, ID numbers) or user‑supplied keywords and returning them as JSON. This makes it trivial to build forms, compliance checks, or automated data entry workflows.

These tools are valuable because they abstract away the complexity of handling different file encodings, image quality variations, and table structures. Developers can simply pass a URL or local path to the MCP client, and the server handles all pre‑processing, OCR, and post‑processing. The result is a consistent API that integrates seamlessly into existing AI pipelines—whether you’re building a chatbot that answers questions about a scanned receipt, an internal tool that parses employee ID cards, or a compliance system that validates invoices.

Real‑world scenarios include customer support bots that read uploaded PDFs for policy information, finance teams that extract key metrics from spreadsheets, or HR systems that auto‑populate employee records from scanned documents. The ability to return Markdown also means the extracted content can be rendered directly in chat windows, preserving structure without additional rendering logic.

What sets TextIn apart is its breadth of supported formats and the unified interface it offers. By combining OCR, Markdown conversion, and structured extraction in a single MCP server, developers can create robust, end‑to‑end document processing solutions with minimal code and zero maintenance of OCR libraries.