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What is the difference between MCP and an API?

With a plain API, the developer reads documentation, writes a client and maps endpoints to functions. With MCP, the client asks the server what tools exist and receives descriptions it can use directly, which is what makes connecting an assistant to an app feel like plugging something in.

What matters here

  • APIs are built for developers, MCP for AI clients
  • MCP exposes tools with descriptions and schemas
  • An API can be wrapped by an MCP server
  • MCP reduces per-client integration work
  • Both still need authentication and permissions

What MCP adds

Discovery. Instead of hard-coding each call, the client reads a list of available tools with names, descriptions and argument shapes, then chooses one. Adding a tool to the server makes it available without shipping a new client.

What it does not change

Security and scoping stay exactly as hard as they were. An MCP server still needs tokens, permission checks and careful limits, because the model calling tools is not a reason to relax any of that.

Where Prysm Note uses it

There is an MCP server so external AI tools can work with your tasks, notes, habits and watchlist, authenticated with a personal access token. The API still exists underneath; MCP is the way AI clients talk to it.

Frequently asked questions

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Disclaimer

This page is general information, not professional, legal, financial or medical advice. It describes common ways of working and how Prysm Note approaches them. Software changes over time, so details may differ from what you see in the product. Any product, company or brand names that appear are the property of their respective owners and are used only for identification. We do not claim any endorsement or affiliation. Where we compare approaches, we aim to describe each one honestly, including where a different approach may suit you better. Try the tools that matter to you and judge for yourself.