"PDF text editing and preview tools" matching MCP servers:

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.

mcp using PyPDF2 to: • merge-pdfs • extract-pages • search-pdfs • merge-pdfs-ordered (merge in user spec. order) • find-related-pdfs (regex extracted text for related PDF files)

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

pdf-tools-mcp

A comprehensive tool server for reading, merging, and extracting content from PDF files via local paths or direct URLs. It enables metadata retrieval, regex searching, and page-specific text extraction with built-in caching and workspace-restricted security.

PDF Tools AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables PDF file manipulation including merging, splitting, extracting pages, extracting text, excluding pages, and reordering pages.

A line-oriented text file editor. Optimized for LLM tools with efficient partial file access to minimize token usage.

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

Provides HTML file preview and analysis capabilities. This server enables capturing full-page screenshots of local HTML files and analyzing their structure.

Enables users to directly edit authoritative Markdown context and tables within Codex, review the complete text before saving, and commit tracked immutable revisions with version history.

An MCP server that provides tools for reading, writing, and manipulating PDF files, including text extraction, metadata retrieval, and merging or splitting documents. It also enables users to create PDFs from plain text and convert specific pages or entire documents into images.

A high-performance Model Context Protocol server that enables AI agents to extract text, images, and metadata from PDF documents using parallel processing. It features intelligent Y-coordinate content ordering to preserve natural reading flow and supports both local files and URL-based sources.

A Model Context Protocol (MCP) server that provides line-oriented text file editing capabilities through a standardized API. Optimized for LLM tools with efficient partial file access to minimize token usage.

MCP server for comprehensive PDF processing including text extraction with OCR, keyword search with regex, table extraction, and page preview as Base64 PNG images.

This server converts PDFs to markdown with intelligent academic paper detection and dual processing engines (marker-pdf for academic content, PyMuPDF for general documents), supporting URL and local file handling, page extraction, batch processing, and PDF link crawling for Claude Code analysis.

An MCP server for local PDF inspection that classifies, searches, extracts text and tables without uploading documents or relying on OCR, surfacing reliability warnings for garbled or scanned content.

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

Enables AI assistants to natively read, edit, and redact PDF documents in place through MCP tools, eliminating manual script execution and layout issues.

An MCP server for reading, rendering, and searching PDF files, specifically optimized for LLMs to extract text, tables, and technical diagrams. It enables metadata retrieval, multi-format text extraction, and page-to-image rendering using PyMuPDF.