"Understanding File System Operations: Read, Write, and Edit Directories" matching MCP servers:

MCP server to read protected (or unprotected) PDF files, extracting text to a temp file, and handling large PDFs.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

A Model Context Protocol server that exposes an airline design system as a queryable knowledge base, enabling AI to discover components, find components for use cases, and scaffold prototypes.

Enables comprehensive local file system operations including searching and reading content from various formats like PDF, Office documents, CSV, and text files. It features automatic character encoding detection and secure path validation for directory access.

A Model Context Protocol server that enables AI agents to access, search, and understand structured package documentation and source code from Git repositories. It automatically generates specialized tools to browse module overviews, components, and detailed documentation for technical libraries.

A local MCP server that lets LLM agents read EPUB books and PDF documents with outline-first navigation, precise node reads, and local SQLite persistence.

Enables PDF reading through MCP with text extraction, Chinese OCR for scanned documents, page rendering, and keyword file search from any compatible MCP client.

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.

Provides AI agents with document conversion to Markdown, intelligently routing small and large files, and enabling targeted extraction via sections, search, and token budgets.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.

Provides structured instructions to Cursor for generating comprehensive system summaries of Node.js/TypeScript codebases.

Provides a real API for coding agents to look up design system components, props, and tokens, preventing guessed answers.

Provides AI agents with component documentation, usage examples, and design tokens from the WordPress Design System, enabling them to follow the latest design system guidance for creating user interfaces.

Model Context Protocol server exposing system prompt files and summaries.

Enables Claude AI to perform comprehensive file operations including reading, writing, notes management, PDF processing, and image handling with thread-safe operations. Provides a complete file management system with enhanced features like document processing and automatic directory creation.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

An unofficial MCP server that gives AI assistants structured access to Italy's Design System .italia, including components, design tokens, usage guidelines, and GitHub issues, updated nightly.

Provides LLMs with real-time access to up-to-date documentation from PyPI, npm, crates.io, GoDocs, DockerHub, GitHub, and GCP, preventing outdated code generation and API hallucinations.

Enables AI assistants to search and retrieve documentation, component specs, theme guides, and CLI commands for the Meta Astryx Design System, providing structured tools and guidelines for coding agents.

Provides access to Appian's Aurora design system documentation via GitHub, enabling LLMs to query components, layouts, and patterns. It supports both public and internal repositories with features for keyword searching and detailed component guidance.