MCP clients compared for GTM work

Most MCP comparisons rank servers. The client matters more, because it sets the limits you actually hit: which protocol features work, which auth versions authenticate, and how much data a single tool result can carry. The same server behaves differently in Claude, ChatGPT, Cursor and VS Code, and only one of them publishes the numbers.

The comparison

Everything below comes from each vendor's own documentation, verified 25 August 2026. Where a cell says "not documented", that means the vendor's MCP docs do not state it, which is a finding rather than a gap in our research.

The most useful column is the empty one

Look at the "max tool result" row. One vendor publishes a number. Everyone else leaves you to discover it by hitting it.

This matters more in GTM than in most MCP use cases, because GTM tools return rows. A code-search server returns a file. A data server returns a hundred companies with a dozen fields each, and dense JSON tokenises badly: every brace, quote and field name costs you. That is the payload shape most likely to hit a ceiling, and it fails quietly rather than loudly. The server returns everything, the client trims to fit, the model summarises what arrived, and nobody is told. The full version of this failure is worth reading before you build a workflow on any client.

Practical consequence: on a client that publishes no limit, ask for twenty rows rather than a hundred until you have established where the edge is, and ask the agent how many rows the tool returned before asking it to analyse them.

The second most useful row is the auth one

Claude's documented auth-spec support is 2025-03-26, 2025-06-18 and 2025-11-25. The current protocol revision is 2026-07-28. Auth support lags the protocol, and it lags differently per client.

That is the mechanism behind the single most common connector complaint: it works for one colleague and not another, with no useful error. Two clients on different auth spec versions, one server built against a specific one. If you are choosing a server, ask which auth spec versions it implements. If you are choosing a client, prefer one that documents the answer.

Notes on each

Claude. The best-documented client by a distance, and for most GTM users the right default. Tools, prompts and resources all work; sampling and resource subscriptions are explicitly unsupported. Two surfaces behave differently: Claude.ai and Desktop carry the larger result budget and a fixed 300-second timeout, while Claude Code has the tighter token budget but makes both it and the timeout configurable via MAX_MCP_OUTPUT_TOKENS and MCP_TOOL_TIMEOUT. If you are pulling large result sets and can work in a terminal, Claude Code is the one where you can raise the ceiling.

ChatGPT. Supported and widely used, and the thinnest documentation of the four on the specifics a data workflow cares about. OpenAI's remote-server guidance recommends OAuth with Client ID Metadata Documents and documents SSE for the streaming interface. There is a meaningful distinction between adding a custom connector for your own workspace and publishing through the Apps SDK, which is a packaged and reviewed path; for GTM use you almost always want the former. Setup availability has varied by plan, so check current terms rather than trusting a guide written six months ago.

Cursor. Supports the widest slice of the protocol on this table, including elicitation, roots and the Apps extension, and all three transports. Config is a JSON file, per project or global, which is a feature for a GTM engineer and a barrier for a rep. If your GTM work already happens next to code, this is the strongest client here.

VS Code. Tools, resources, prompts and MCP Apps, configured through .vscode/mcp.json or the user profile. The docs are firm about not hardcoding credentials and say little else about auth. Reasonable if your team lives in VS Code; nobody should adopt it for GTM alone.

How to choose

Honestly, on where you already work. The feature differences above matter at the margins; the context-switch cost of doing your prospecting in a tool you do not otherwise open matters every day.

• Reps, founders, anyone non-technical: Claude's hosted surfaces. Connector UI, OAuth, documented limits.
• Large result sets: Claude Code, because the ceiling is configurable.
• GTM engineers already in an editor: Cursor.
• Whole team standardised on Microsoft tooling: VS Code.

What to test before committing

Four checks, twenty minutes, in whichever client you picked:

1. Connect and list tools. Ask the agent what tools it can see. If it lists none, the connector was added but not authorised.
2. Ask for a known row count. Request twenty results and have it tell you how many arrived. Repeat at fifty and a hundred. You have now found the ceiling nobody published.
3. Run one real query from your actual ICP, not a demo query. Coverage gaps show up on real filters.
4. Revoke and reconnect. Confirm you can cut access without breaking your other clients. If you cannot, you are on a shared API key and should fix that first.

Related reading

• MCP for sales for the wider picture.
• Why your prospecting agent silently drops results on the limits in detail.
• MCP security for revenue teams on the auth questions to ask a vendor.
• The best MCP servers for sales for the other side of the stack.

Sources

All verified 25 August 2026.

• Anthropic, Building custom connectors.
• OpenAI, MCP documentation.
• Cursor, Model Context Protocol.
• Visual Studio Code, MCP servers.
• Model Context Protocol, Versioning.