"How to Read Files Using a Computer" matching MCP servers:

Enables LibreChat agents to manage per-user private files, persistent documentation, RAG indexing and semantic search, and publish files via secure opaque public links.

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

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.

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

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Converts Markdown files to Atlassian Document Format and publishes them to Confluence, with support for rendering Mermaid diagrams as PNG attachments.

Converts any OpenAPI/Swagger spec into an MCP server, exposing REST API endpoints as tools for Claude.

Enables converting Markdown text into clean HTML for headings, lists, code blocks, tables, links, and images, with optional full-document wrapping via x402 micropayments.

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Enables local conversion of PDFs to Markdown, with automatic OCR fallback for scanned pages, image extraction, and page-by-page structure preservation.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Converts Markdown files and raw content into professionally styled PDFs with full support for Mermaid diagrams and syntax highlighting. It offers customizable page formats, margins, and modern typography for high-quality document generation.

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 clients to search live documentation for popular developer libraries and return clean, source-cited summaries via a RAG pipeline.