Remote vs local MCP servers: which should you use?
Published November 4, 2026
Use a local MCP server when the tool needs your machine: files on disk, a local database, a command line tool. Use a remote MCP server for cloud services such as Gmail, Slack or GitHub: it works in web and mobile AI apps, signs in with OAuth instead of keys in a config file, and keeps running when your laptop is closed.
What “local” and “remote” mean in MCP
A local server is a program your AI app starts on your computer. The two talk over standard input and output (the stdio transport). It has the same access as any program you run.
A remote server is a web service. The AI app connects to it by URL over HTTP (the Streamable HTTP transport in the current MCP specification) and signs in with OAuth, the same way you sign in to an app with Google.
Where each works
Local servers work in desktop apps and coding tools that can start programs: Claude Desktop, Claude Code, Cursor, VS Code, Codex, Gemini CLI. They do not work in a browser tab or on a phone.
Remote servers work in those tools and also in Claude on the web and on mobile and in ChatGPT, because nothing has to run on your device.
Security trade-offs
Neither is automatically safer. The questions to ask are the same:
- Where do the credentials live? Local servers often read API keys from a config file in plain text; a good remote server stores them encrypted and never shows them to the AI.
- Who can change what the server does? A local package updates when you reinstall it; a remote server is updated by its operator.
- Can risky actions be held for approval? That depends on the server, not the transport.
Our recommendation
Keep local servers for local things: your files, your terminal, a database on your machine. For cloud services, use remote servers, ideally one hub that holds all your accounts, so the same setup works in every AI app you use.
Manyplug is a remote MCP hub: 48 services built in, several accounts per service, one URL for Claude, ChatGPT, Cursor and the rest.