"A file opener for reading PDF files, images, and other file types" matching MCP servers:

Local-first filesystem MCP bridge with ripgrep search, atomic writes, multiple transports

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 fast file search on macOS using the native mdfind (Spotlight) command, with support for filtering, regex, sorting, and limiting results.

A Model Context Protocol server that enables AI agents to read, search, and extract content from PDF files.

Converts Markdown files to Word (.docx) and PDF documents. Supports .dotx templates for branded styling and batch conversion.

Memory-efficient MCP server for reading and splitting large PDF files page by page using PyMuPDF.

Provides PDF reading, text search, navigation, and form filling capabilities through MCP, with cross-platform PDF viewer integration for seamless document interaction.

An MCP server for high-quality bidirectional PDF ↔ Markdown conversion with full Unicode/CJK character support, enabling users to convert files via natural language commands.

Full-stack PDF intelligence MCP server for extracting, manipulating, annotating, converting, validating, and RAG-searching PDFs through a unified tool surface and React workbench.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables AI agents to perform local-first PDF processing entirely on-device, including OCR write-back to make scans searchable, unlocking and re-encrypting PDFs, splitting/merging/rotating pages, and compressing files, with no cloud calls or file uploads.

Enables AI models to perform file operations, user management, automations, and more within Files.com's secure file transfer platform via the Model Context Protocol.

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

A Model Context Protocol (MCP) server that provides comprehensive PDF redaction capabilities, including text and image redaction, search, and session-based in-memory operations using FastMCP and pymupdf.

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

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Converts dense PDFs into soft, minimal, card-based HTML readers with preserved source text, rendered pages, and cropped tables/figures as images, all processed locally.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.

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.