"High-Quality PDF Extraction to Text with Tokenization and Accurate Processing of Complex Layouts" matching MCP servers:

An MCP server that provides a tool to extract text content from local PDF files, supporting both standard PDF reading and OCR capabilities with optional page selection.

Enables AI agents to read and analyze PDF documents for natural language Q\&A. Supports multiple LLM providers including Google Gemini, Anthropic Claude, and OpenAI.

The local PDF workflow for Claude Desktop and MCP hosts: fill, sign, merge, split, extract, and analyze PDFs without sending files to a web app.

Algorithmic text and NLP analysis server providing sentiment, readability, keyword extraction, language detection, stats, and more via REST and MCP.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

A PDF processing server that extracts text via normal parsing or OCR, and retrieves images from PDF files through the MCP protocol with a built-in web debugger.

Enables fast text classification using Model2Vec static embeddings with 10 default categories (technology, business, health, etc.), supports custom category management, batch processing, and provides both local and remote deployment options.

An MCP server that enables users to read, search, and analyze PDF documents. It provides tools for extracting text, viewing metadata, searching content with context, and generating word statistics.

A local document processing toolkit for AI agents that extracts text, converts PDFs to Markdown, merges files, extracts tables, and summarizes documents without external API dependencies.

A Model Context Protocol server for managing text notes, with resources (note:// URIs), tools (create_note), and prompts (summarize_notes).

An MCP (Model Context Protocol) server specialized in deciphering PDF internal structures.

Provides comprehensive document processing, including reading, converting, and manipulating various document formats with advanced text and HTML processing capabilities.

Counts characters and words in both Japanese and English text files, with special handling for Japanese morphological analysis and proper character counting excluding spaces and line breaks.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Provides comprehensive text analysis capabilities including character counting, word statistics, character type analysis, and text length validation for Korean and English text. Supports AI agents in analyzing and validating text content with detailed statistics and Unicode support.

Enables reading and extracting content from PDF documents including text (as Markdown), images, tables, and metadata from both local files and URLs, with OCR support for scanned documents.

Enables comparison of baseline and counter-party contract clause revisions, flags high-risk shifts in indemnity, IP assignment, liability caps, and non-solicitation, and generates legal redline summaries with severity and escalation verdicts.

A Model Context Protocol server that enables Claude to fetch, process, and extract information from PDF documents, including LaTeX mathematical equations.

Enables Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.