Does ChatGPT Have Connectors Like Claude?
Both ChatGPT and Claude offer connectors for Team and Enterprise plans, but they work somewhat differently. This guide compares how each connects to tools and sources, what read or write access means in each case, and how a shared work record bridges both.
Updated 5 min read
Yes, ChatGPT has connectors, and they serve a similar purpose to Claude's: they let an AI assistant search and read from connected content sources such as Google Drive, SharePoint, and other services. The mechanics differ in meaningful ways, and the access model for each is worth understanding before you choose an approach. For teams that use both assistants, a shared work record that both can read is the practical answer to the connector gap.
Tools like fenbs sit outside both AI apps. Claude, ChatGPT, Cursor, and other supported tools all connect to the same project context over MCP, so switching between them does not mean starting the work explanation from scratch.
| Feature | ChatGPT connectors | Claude connectors |
|---|---|---|
| Plans that include them | Team and Enterprise plans | Team and Enterprise plans |
| Supported sources | SharePoint, OneDrive, Google Drive, and others depending on plan and region | Google Drive, Microsoft 365, and others depending on plan |
| What the assistant does with connected content | Searches and reads from connected sources to inform its answers | Searches and reads from connected sources to inform its answers |
| Write or publish access | Read-only for knowledge sources; write access available through Actions and the Responses API | Read-only for knowledge sources; write actions require a custom MCP integration |
| Developer integrations | Actions in GPTs, the Responses API with tool use | MCP: the Model Context Protocol standard, plus the Anthropic API |
| Shared work record across AI apps | Not built in; requires an external tool | Not built in; requires an external tool such as fenbs |
How Claude connectors work
Claude connectors, available in Team and Enterprise plans at claude.ai, let you attach content sources to a Claude workspace. When you ask Claude a question, it searches those connected sources and cites what it found. The connection is read-only: Claude can read and summarize, but cannot modify the files in a connected source through the connector itself.
For developer integrations, Claude supports MCP (the Model Context Protocol), an open standard that lets AI apps connect to external tools, services, and data sources. An MCP server can give Claude both read and write access to whatever it exposes. This is a separate layer from the built-in connectors: connectors are configured in the organization settings, while MCP integrations are set up per user or per deployment.
For a full explanation of how Claude connectors work and how to set them up, see Claude connectors explained.
How ChatGPT connects to tools and sources
ChatGPT Work (available on paid plans) and ChatGPT Team and Enterprise include connectors for connected content search. These operate similarly to Claude's built-in connectors: the assistant searches your connected sources and uses the results to inform its answers. The specific sources available depend on the plan and your organization's configuration.
ChatGPT also supports tool use through the Responses API and through Actions in custom GPTs. Actions allow a developer to connect ChatGPT to an external API so it can take actions, not just read. This is functionally similar to what an MCP server does for Claude. Check OpenAI's documentation for the current set of supported action patterns and authentication options.
For a practical look at ChatGPT connectors and apps, that page covers the setup and the most common configurations.
Key differences in how access works
The main practical differences between ChatGPT and Claude connectors come down to the developer integration model and what each assistant does by default when access fails.
- Claude uses MCP as its standard for developer-built integrations. MCP is an open specification, so third-party servers and clients can implement it without being tied to Anthropic's platform.
- ChatGPT uses OpenAI's Actions and API patterns for developer integrations. These are specific to OpenAI's ecosystem and require following OpenAI's schema for tool definitions.
- Both assistants search connected sources; neither automatically decides when to use them versus its own training. You may need to prompt the assistant to check connected sources explicitly.
- Write access through either assistant requires a custom integration (an Action for ChatGPT, an MCP server for Claude) rather than the built-in connectors.
When to use ChatGPT connectors, when to use Claude connectors
The choice between the two often comes down to which AI assistant your team prefers for the work, not which connector system is technically superior. Both give you read access to the same kinds of enterprise content sources. The meaningful differences emerge at the edges: developer integrations, long-context handling, and the assistant's behavior on specific kinds of tasks.
If your team uses both, the more important question is whether the underlying work record is consistent across both tools. A decision made in a ChatGPT session should be visible to the Claude session that continues the same project. That consistency requires a work record outside both AI apps.
For a deeper comparison of the two assistants on everyday work, see Claude vs ChatGPT and ChatGPT to Claude migration.
One work record, readable by both ChatGPT and Claude
fenbs connects over MCP to Claude, ChatGPT, Cursor, Codex, and other supported AI apps. Each reads the same projects, decisions, rules, and Where we left off before starting, and saves progress for whoever works next. Switching assistants does not lose the work.
Create a free accountFree for one person · No credit card · Works with Claude, ChatGPT, Cursor and more
How to do this with fenbs
- Create a free account and add the project you want both assistants to work on.
- Write the approved decisions, rules, and current task status in fenbs. This becomes the shared starting point.
- Connect Claude over MCP from Integrations. Follow the same guide for ChatGPT. Both read the same fenbs project.
- Before switching from one assistant to the other, ask the current one to save progress in fenbs: what it completed, what remains, and the next step.
- Open the next session in the other assistant and ask it to read the project context before starting. It picks up from the same point.
fenbs is free for one person. A team workspace adds roles so different people can control what each connected assistant can read and update.