Definition
An MCP client is the AI application or runtime that connects to an MCP server and uses its tools.
The client might be a desktop assistant, an IDE, an internal agent, or a chat interface. It asks the server which tools are available and uses those tools when the model decides a task needs external capability.
The client does not need to know every detail of the upstream API or database. It needs a server URL, authentication, and a useful tool catalog.
Typical client flow
The client discovers tools first, then calls them with structured arguments.
- Configure the MCP server URL.
- Send the required authentication headers or token.
- Call tools/list to discover available tools.
- Let the model choose a tool when the task requires it.
- Send structured arguments to the selected tool.
- Use the tool result in the next response or workflow step.
Test clients
A simple test client is useful before wiring a full desktop assistant or IDE.
Teams often start with a small client or command-line smoke test to confirm tools/list works, authentication is correct, and the expected tools are visible.
That early check catches simple mistakes before a model is asked to choose and call tools inside a longer workflow.
Common questions
Does an MCP client need database credentials?
Usually it should not. A safer design keeps database credentials on the server side and gives the client a scoped way to call approved tools.
Can different clients use the same MCP endpoint?
Yes. The same published MCP surface can be used by multiple compatible clients when they have the right URL and token.
What should I test first in an MCP client?
Start with tools/list. It confirms the server URL, token, publication state, and resolver are working.