MCP Client: The AI App That Calls the Tools

An MCP client is the AI application on your side of the conversation — the app that connects to MCP servers, reads their tool lists, and calls tools on your behalf. Claude is a client. So are ChatGPT, GitHub Copilot, Cursor, Gemini CLI and OpenCode. The client is whichever assistant you already pay for; MCP's whole contribution is that they all plug into the same connectors.

That has a consequence buyers rarely notice: your client choice and your connector choice are independent decisions. The connector that lets Claude read and run your Google Ads account is the same one that lets ChatGPT run it — same address, same tools, same limits.

How an MCP client works

The client does four jobs in every tool-using conversation:

1. Discovery. On connect, it fetches the server's tool list — names, descriptions, input schemas — and hands it to the model as context.
2. Selection. Mid-conversation, the model decides a tool would help ("which search terms wasted spend?" needs a query tool) and drafts a call with arguments.
3. Mediation. The client executes the call against the server — and for writes, most clients stop first and show you exactly what is about to run. This is where tool calling meets human judgement.
4. Rendering. Results come back as structured data; the model turns them into the answer you read.

The model never touches your account directly. It emits a request; the client transports it; the server executes. Every layer is inspectable, which is what makes the whole arrangement auditable.

Client differences that actually matter for ads work

Feature checklists mislead here. Three differences do the real discriminating:

• Approval behaviour. Claude surfaces each write as a permission prompt naming the tool and its arguments before anything runs. Other clients range from per-call prompts to configurable always-allow. For a system touching spend, the prompt is the safety feature — know your client's default before you connect an ad account.
• Transports. Remote connectors run over streamable HTTP — a URL you paste. Older or local-first setups launch servers as processes on your machine. Every major client now handles remote URLs; a few still lag on auth details.
• Tool budgets. Clients differ in how many connected tools they handle gracefully and how well the model picks among them. A focused connector — a few dozen ads tools — behaves better in every client than a junk drawer of hundreds.

Choosing a client is choosing an approval experience

Choosing a client for ads work is mostly choosing an approval experience. The analysis is identical everywhere — same tools, same account data, same answers. What differs is the moment before a budget changes: what you see, how legible it is, and whether always-allow is one careless click away.

A sane default: run reads in whichever client you live in daily, and hold writes to the client whose approval prompts you find clearest. Since the connector is portable, trying two clients side by side costs nothing but a second paste of the same address. The client compatibility page keeps the current tested list, and the MCP server entry covers the other half of the handshake.