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What are MCP servers for?

MCP lets a compatible AI application use data and functions from external systems. This guide takes you from choosing a server to checking your first connection.

What does MCP mean?

MCP stands for Model Context Protocol. It defines how an AI application communicates with a program that provides data or actions. MCP is not an AI model, and connecting a server does not retrain the model.

For example, a document search server could help an assistant find passages relevant to your question. What the assistant can read or change depends on the server, the application and the permissions you grant.

The parts of a connection

AI application

This is where you enter your task and read the result. It must support the connection method used by your chosen server.

MCP client

This component handles communication with the server. Your AI application usually manages it for you.

MCP server

It provides data and callable functions. It may run on your computer or on the provider’s infrastructure; the setup differs accordingly.

Choosing a server

Start with the task: do you want to search documents, query a database or use a function from an external service? Open the MCP catalogue, search for that task and read the details of a suitable entry.

Check the provider, linked documentation or source code, installation requirements and any fees. Opening a catalogue entry does not install software or establish a connection. Check compatibility in the documentation for both your client and the server.

Connecting step by step

1. Read the connection instructions

Look for a remote address or local startup instructions on the detail page. If information is missing, consult the provider’s documentation.

2. Set it up in your AI application

A remote server usually needs an address and may require sign-in. A local server may need installation and a startup command. Follow your client’s setup instructions.

3. Review permissions

Check which data and actions the connection can access. Grant only the access needed for your task.

4. Try a simple query

Begin with a small task you can verify, such as retrieving a public fact. Compare the answer with its source before using the connection for more complex work.

Example: looking up model information

The DevFlow MCP server listed in the catalogue provides tools for querying the model catalogue and ranking. With a suitably configured client, you could compare the available information about two models. Looking up their details is separate from running either model.

If the connection fails, check the address, authentication and the client’s error message. For a local server, also check that the required program is running. Do not share secret keys in public messages.