What is MCP? Letting your AI assistant use real tools

What is MCP? MCP, the Model Context Protocol, is an open standard that lets AI assistants use real tools and data. Instead of every AI app building a custom integration for every service, a service offers one MCP server and any MCP-capable assistant can connect to it. The result is an assistant that can act, such as searching your files, creating a design or updating a record, rather than only telling you how.

Anthropic introduced MCP as an open standard in November 2024, and it has since been adopted by a growing number of AI applications and developer tools. The official MCP site describes it as a universal way to connect AI applications to external systems, and compares it to a USB-C port for AI.

How MCP works: hosts, clients and servers

MCP has three roles. You only ever deal with the first and third directly.

Each server can offer three kinds of thing. Tools are actions the assistant can take, such as "create a design". Resources are data it can read, such as a file or a brand profile. Prompts are ready-made instructions the server suggests for common jobs. Servers can run on your own computer, talking over standard input and output, or on the web, talking over HTTP.

What happens when an assistant uses a tool

Behind a simple request, the steps are always the same. It helps to know them, because each one is a place where you stay in control.

1. 1

   The assistant learns what's available

   When it connects, the client asks each server for its list of tools, with a name, a description and the inputs each one takes.

2. 2

   You ask for something

   For example: make a story announcing that we open late on Fridays.

3. 3

   The assistant chooses a tool

   It decides that a design tool fits and fills in the inputs from your request. Many apps ask your permission before a tool runs.

4. 4

   The server does the work

   It calls the real service with the credentials you gave it, and only with the permissions those credentials allow.

5. 5

   The result comes back

   The server returns the outcome, such as a link to the new design, and the assistant tells you what it did.

{
  "jsonrpc": "2.0",
  "id": 7,
  "method": "tools/call",
  "params": {
    "name": "design",
    "arguments": {
      "request": "A story announcing that we open late on Fridays",
      "size": "ig-story"
    }
  }
}

What MCP makes possible for design

Most design work is a chain of small steps across several apps. MCP lets an assistant carry that chain for you, inside the tools you already use, while you keep the final say.

The quality still depends on the tool at the other end. An assistant connected to a design tool with a strong brand system produces on-brand work; one connected to a blank canvas produces generic work. AI design tools covers how to judge that, and brand guidelines for AI shows how to give an assistant rules it can follow.

Staying safe with MCP

Connecting an assistant to a real service means it can change real things. Treat an MCP connection like giving a capable new colleague access: specific, limited and easy to take back.

• Use scoped keys. Create a key that allows only what the task needs, such as reading designs but not claiming anything.
• One key per place. Name each key after where it is used, so you can revoke one without breaking the others.
• Keep keys secret. Store them in a password manager or the client's secure settings, never in shared files or screenshots.
• Review before approving. Read what a tool is about to do, especially when it creates, changes or spends something.
• Be wary of untrusted content. Text an assistant reads through a tool, such as a web page or a document, can contain instructions. Keep sensitive tools off when working with material you don't trust.
• Revoke what you don't use. Old keys are risk with no benefit.

Gradiently and MCP

Gradiently runs a hosted MCP server at https://gradiently.design/api/mcp. Create a key in Settings under API and agents, choose what it can do (such as reading designs, creating and editing designs, searching Marks or generating brands) and add it to your MCP client. The key is shown once and can be revoked at any time. Your assistant can then search Marks, read your workspace, generate brand options and make designs that open in the Studio for you to finish.

{
  "mcpServers": {
    "gradiently": {
      "url": "https://gradiently.design/api/mcp",
      "headers": { "Authorization": "Bearer YOUR_KEY" }
    }
  }
}

For a walkthrough of what that looks like in practice, see designing with Claude. For step-by-step setup in different clients, see connecting an AI assistant and the developer docs.