Files and storage
AWS S3
By Amazon Web Services
Amazon S3 is handled through the managed AWS MCP Server, which lets AI run scripted AWS actions, create presigned links and search AWS docs.
- Official
MCP server category
Files and storage MCP servers
Let assistants find and read the documents your team already stores.
- 6 MCP servers
Most company knowledge sits in shared drives. File and storage servers let an assistant search those drives, read documents and, where allowed, create or move files. That powers questions like "find the latest version of the supplier contract" and workflows that file incoming documents automatically.
Drives often hold sensitive files. The assistant should see only what the connected user can see, and ideally only the folders a task needs.
Files and storage
All files and storage mcp servers
Files and storage
Box
By Box
Box's official MCP server lets AI search and read files, ask questions across documents with Box AI, extract data and upload files.
- Official
Files and storage
Dropbox
By Dropbox
Dropbox's own MCP server lets AI list, search and read files, convert them to markdown and create, move, share and delete files. In beta.
- Official
Developer tools
Filesystem
By Model Context Protocol project (Anthropic reference servers)
The MCP project's Filesystem reference server lets AI read, write, edit, move and search files, only inside folders you allow.
- Official
Files and storage
Google Drive
By Google (Google Workspace)
Google's own Drive MCP server lets AI search, read and create files in Google Drive, with your Google Workspace sign-in.
- Official
Files and storage
OneDrive
By Microsoft
Microsoft's OneDrive MCP server, part of its Work IQ preview, lets AI find, read, create, move, share and delete files in OneDrive.
- Official
How to choose
How to choose in this category
Prefer servers that use the vendor's own sign-in and respect existing sharing permissions. Start with read access, connect a service account limited to specific folders and log what is accessed.
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Related on ExecMedia
Related services
View all related services- MCP integration Connect AI assistants to your CRM, files, databases and tools through Model Context Protocol servers, with safe permissions.
- RAG knowledge assistants Assistants that answer questions from your own documents and show where each answer came from.
- Customer portals A secure place where your customers upload documents, check status, pay and message your team.
- Document automation Read invoices, forms, contracts and IDs, pull out the right fields and route them for review.
- AI Product Development AI agents, knowledge assistants, copilots and document automation built into the way your team already works.
Solutions
View all solutions- Knowledge assistant (RAG) Ask a question in plain words and get an answer from your own documents, with links to the sources.
- AI document processing Read forms, applications, IDs and statements, extract the fields you need and route each document for the right review.
- Automated quoting Draft accurate quotes and proposals from a request, your price rules and past work, for a person to approve.
- Contract review assistant Highlight unusual clauses, missing terms and deviations from your standard positions, so reviewers focus where it matters.
- AI translation workflows Translate websites, products and support content quickly with AI, a shared glossary and native-speaker review where it matters.
- Internal help desk assistant An assistant in Slack or Teams that answers policy and how-to questions from your handbooks and opens tickets when needed.
Industries
View all industries- Legal Contract review assistants, knowledge search, intake and document automation for law firms and in-house legal teams.
- Healthcare Patient booking, intake forms, internal knowledge assistants and admin automation for clinics and care providers.
- Insurance Claims intake, document and photo processing, policy knowledge assistants and customer portals for brokers and insurers.
Guides and articles
View all guides and articlesAI models
View all ai models- Claude Sonnet 5 Anthropic's balance of speed and intelligence: a strong everyday model for assistants, document work, tool calling and coding.
- Embeddings Models that turn text into vectors for search, retrieval, clustering and recommendations.
- Open weights Models whose weights you can download and run on your own servers or a cloud of your choice.
- Gemma 4 Google's open-weight model family under Apache 2.0, in sizes from phone-friendly to 31B, with image input and function calling.
- Gemini Embedding 2 Google's current embedding model, multimodal: it embeds text, images, video, audio and PDFs for search and retrieval.
- Llama 4 Scout An open-weight Llama 4 model with image input and a very long context window, for teams that want to host a capable model themselves.
Glossary terms
View all glossary terms- Embeddings Embeddings are lists of numbers that represent the meaning of text or images, so software can find items that are similar in meaning.
- Hallucination A hallucination is when an AI model states something false or invented as if it were true, such as a made-up fact, figure or source.
- Model Context Protocol The Model Context Protocol, or MCP, is an open standard for connecting AI assistants to external tools and data in a consistent way.
- Open-weights model An open-weights model is an AI model whose trained parameters are published, so anyone can download and run it on their own hardware under its license.
- RAG RAG, or retrieval-augmented generation, is a method where an AI system first finds relevant passages in your documents, then answers using only those passages.
- Semantic search Semantic search finds results by meaning rather than exact words, so a search for "reset my login" can find an article titled "Forgot your password".