What is MCP and how do you give ChatGPT, Claude or Grok memory with your own data?

MCP (Model Context Protocol) is an open standard that lets assistants like ChatGPT, Claude or Grok query external data and tools, such as a workout log or a list of recipes, without having to copy them into every conversation. It is the most direct way to give your AI a memory built on your own data.

At Traiker we came to MCP through a very everyday frustration: every chat with an assistant starts from scratch. One of us lived it every time he asked what to have for dinner before a leg day and had to explain his routine all over again. If that sounds familiar, this article is for you.

What is MCP?

Anthropic released it as open source on 25 November 2024. They wanted to solve a problem that the announcement itself describes very well: models are isolated from data, trapped behind information silos.

The official documentation compares it to a USB-C port for AI applications. You connect to your data once, and any compatible assistant can use that connection, instead of building an integration for each one.

How does it work?

The specification separates the application you use (the host, such as Claude or Cursor) from the MCP server, which provides access to the information. The server offers resources that the model reads, tools it can run and reusable prompts. A resource might be your history of gym sessions; a tool might be “log a meal”. The server can live on your computer or online, and the assistant only sees what that server decides to expose.

When you ask something, the assistant decides whether it needs your data, queries only what it needs and answers with that in front of it.

Which assistants support it?

It stopped being “Anthropic's thing” very quickly. Claude supports custom connectors with remote MCP, OpenAI documents remote MCP servers as tools and xAI offers remote MCP tools for Grok.

Interest is also noticeable in Spain: in Google Trends over the last twelve months, “que es un mcp de ia” appears as a rising search.

How do you give your AI memory?

There are three paths. The first is to use ready-made servers for Drive, Notion or GitHub; it is quick if your data already lives there, but it usually ends up spread across many places in different formats. The second is to build your own server with the official SDKs: it gives you total control, but also all the responsibility for the database, authentication, encryption and backups.

The third is the one we are building at Traiker: your own database for each person, templates for gym, meals or CRM, and an MCP server designed to connect to your assistants; we're opening access gradually in the beta. You can see a real example in how the team keeps its gym and meal log with AI.

What should you demand first?

Before connecting a server, ask yourself who stores the data and where, whether it is encrypted, what the assistant can read and what it can change, and whether you can disconnect it in one click. Tools that write data should ask for confirmation before touching anything, and you should only connect servers from people you trust, because they can act on your behalf. We cover this in more detail in how to give your data to an AI without losing control.

Frequently asked questions

Does MCP only work with Claude?

No. Anthropic created it, but it is an open standard and OpenAI and xAI document how to use it with their platforms.

Do I need to know how to code?

To create a server, yes. To use one that already exists, it is usually enough to add its address in the assistant's connector settings.

Is it the same as ChatGPT's memory?

No. That memory stores fragments of your chats inside one application. With MCP, your data stays yours, it is structured and it works across several assistants.

If you want to try Traiker before anyone else, sign up for the beta.