"A tool to extract or read text and images from PDFs" matching MCP servers:

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

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.

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

A universal MCP tool gateway that manages multiple remote tool processes, enabling LLMs to dynamically invoke web scraping, summarization, and knowledge retrieval through standardized Function Calling.

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.

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.

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

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.

Enables LLM clients to search a firm's precedent vault and draft grounded contract clauses, legal memos, and document summaries.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables reading and extracting content from WeChat public account articles using browser automation, allowing AI models to analyze and summarize WeChat articles through natural language requests.

A Model Context Protocol server that allows AI assistants to discover, load, and process local documents on Windows systems, with support for multiple file formats and OCR capabilities for scanned PDFs.

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.

Turns plain text or Markdown, web pages, and local PDFs into editable Markdown outlines that can be rendered as standalone, offline-capable interactive HTML mind maps. Works with any MCP client with no API key required, since the connected model writes the final outline from a draft and cleaned source text.

Enables fetching, searching, and summarizing YouTube video transcripts with multi-language support.

Enables counting characters or bytes in text with options to include or exclude whitespace. Provides a simple tool for text analysis and length measurement.

This server provides a tool to generate unified diffs between two text strings, facilitating text comparison and analysis.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

Provides tools to summarize README files from local paths or public Git repositories into structured JSON summaries. It enables users to quickly extract key facts and project overviews from documentation through automated tool calls.