#MCP client architecture

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grim talon
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Hey all - would appreciate some help on a technical question.
For both Claude and ChatGPT, who is the actual MCP client in the web app and the desktop app? Do those clients connect directly to an MCP server, or is there some proxy/bridge layer in between?
If they don’t connect directly, why, and what’s the way to connect to a private MCP server?

edgy garnetBOT
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Hi @grim talon. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

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For ChatGPT, the actual MCP client is not the user's web or desktop app itself, but rather OpenAI's backend infrastructure. When you configure a connector or remote MCP server in ChatGPT (via the web or desktop app), the model and its backend runtime act as the MCP client. The user's browser or desktop app does not connect directly to the MCP server—instead, requests are routed through OpenAI's servers, which handle the MCP protocol and tool calls on behalf of the user.

This architecture is confirmed by several sources:

  • The OpenAI documentation states that when using the Responses API or ChatGPT, you declare the MCP server in your configuration, and the OpenAI runtime (not the client/browser) connects to the MCP server.
  • The MCP tool guide explains that the model interacts directly with the MCP server, but this is orchestrated by the OpenAI backend, not the user's device.
  • For security and privacy reasons, OpenAI recommends connecting only to trusted MCP servers, as all data flows through OpenAI's infrastructure before reaching the MCP server, and not directly from the user's device to the MCP server. This is also why OAuth flows and approvals are managed by OpenAI's backend, not the client app itself Risks and safety.
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If you want to connect to a private MCP server, you must make it accessible to OpenAI's backend (i.e., it must be reachable from the public internet, or at least from OpenAI's servers). You then register the MCP server in ChatGPT's settings or via the API, and OpenAI's backend will handle the connection and tool calls Test and connect your MCP server.

For Claude, while the knowledge sources do not provide detailed information about its architecture, a forum post notes that Claude and ChatGPT differ in their handling of MCP discovery endpoints, but both act as the MCP client from their respective backend infrastructures—not from the user's browser or desktop app. Claude's backend, like OpenAI's, is responsible for connecting to the MCP server, not the user's device Forum post: Trouble with ChatGPT Connector OAuth.

Summary:

  • The MCP client is the backend (server-side) infrastructure of ChatGPT (and Claude), not the user's web or desktop app.
  • The client apps do not connect directly to MCP servers; all traffic is routed through the model provider's backend.
  • To connect to a private MCP server, it must be accessible to the backend, and you configure it via the app or API.

If you need more details about Claude's architecture, the knowledge sources do not provide further specifics.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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@grim talon Kapa.ai is still learning and improving, please let me know how I did by reacting below.

grim talon
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@edgy garnet why it's architectured that way? why not using the client - either desktop app or web app as mcp client

edgy garnetBOT
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Let me check the knowledge base for you again. One moment! :books:

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The knowledge sources do not provide a detailed, explicit rationale for why OpenAI architectures MCP client connections through their backend rather than directly from the client (web or desktop app). However, several strong reasons are implied throughout the documentation:

  1. Security and Data Privacy
    Routing MCP connections through OpenAI’s backend allows for centralized enforcement of security controls, such as approval flows, logging, and data boundary protections. This setup helps prevent sensitive data from being exposed to untrusted environments and enables OpenAI to implement safeguards against prompt injection and data exfiltration attacks. Direct client-to-MCP connections would make it much harder to enforce these protections and could expose sensitive credentials or data to the client device or browser, which is not recommended Risks and safety Best practices for API key safety.

  2. Approval and Monitoring
    The backend architecture allows OpenAI to require explicit approval for sensitive tool calls, log all interactions, and provide organization-level controls. This would be difficult to guarantee if the client app connected directly to MCP servers, as client-side environments are less trustworthy and harder to monitor Risks and safety.

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  1. Network Accessibility
    Many MCP servers are not accessible from arbitrary client devices due to firewalls, VPNs, or private network configurations. By routing through OpenAI’s backend, which is publicly reachable, it’s easier to ensure reliable connectivity to MCP servers Guide to Using the Responses API's MCP Tool.

  2. API Key and Credential Safety
    Exposing API keys or sensitive credentials in client-side environments (like browsers or desktop apps) is strongly discouraged, as it risks credential theft and unauthorized access. OpenAI’s backend can securely store and use these credentials without exposing them to the client Best practices for API key safety.

In summary, the architecture is designed this way primarily for security, privacy, monitoring, and reliability reasons. Direct client-to-MCP connections would undermine these goals and introduce significant risks.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon: