A lot of people have found their AI of choice. But choosing one today doesn’t mean you want to be locked into it tomorrow.
Once AI becomes part of your daily work, switching involves more than opening a different chat window. You’ve connected apps, figured out workflows, and given an assistant access to the information it needs. Setting all of that up again every time you try another product gets old.
Tool aggregators can make switching easier. They keep your connections to other apps in one place, giving compatible AI products a shared way to access them. It’s a useful approach, but it comes with trade-offs around security, reliability, and who you depend on.
Why I built my own
I started with a popular hosted tool aggregator. It generally worked, but I wasn’t happy with the experience. After years of building products, I could see gaps in how things were put together.
At first, my frustrations were about usability. Over time, they made me look more closely at permissions, access, and how much trust I was putting in the service. UX concerns became security questions. Eventually, I decided to build my own.
That paid off when I moved from Claude Cowork to ChatGPT Codex. I reconnected my one custom connector, and my tools were available again. I didn’t have to set up each integration individually.
That’s the appeal for me. The work I’d already put into connecting my tools carried over when I changed AI products.
Hosted convenience comes with trust
Hosted aggregators take care of much of the setup and maintenance. If you want your AI connected to several apps without managing the infrastructure yourself, that saves a lot of work.
But an aggregator can also become a concentrated point of access. Depending on how it works, you may be trusting it with credentials or permissions across several services. If something goes wrong, the consequences could reach beyond the aggregator itself.
That doesn’t mean every hosted service is insecure. It means you should look closely at what you’re handing over. What permissions does it request? Can you limit that access? Can you revoke it easily? Does the provider clearly explain how it handles your credentials?
Running your own changes that arrangement. You get more control over how connections are managed, but keeping the system secure and maintained becomes your job. Self-hosting gives you more control; how secure it is depends on how well you run it.
Connections are only part of lock-in
An aggregator helps with tool connections. It doesn’t automatically bring your chat history, saved context, preferences, or workflows into another AI product.
Those things can matter just as much as the integrations. An assistant with months of context about your work can be hard to replace, even if the new one has access to all the same apps.
My switch was easier because my connections carried over. That doesn’t mean every part of my AI setup did.
It’s worth being clear about what an aggregator solves. It removes some of the friction of switching, but it doesn’t make your whole AI setup portable.
The same tools can behave differently
Giving two AI products access to the same tools doesn’t mean they’ll use them the same way.
They may choose different tools, interpret instructions differently, or need more guidance. A workflow you trust in one product may take some adjusting in another.
There’s also a difference between letting an AI read something and letting it act on it. Reading a document, editing it, and sharing it are separate capabilities with different consequences.
A shared connector makes access convenient. You still need to know what each AI can do with that access, and whether your aggregator lets you set the limits you want.
The aggregator becomes another dependency
Moving your connections outside an AI platform adds another service to your setup.
What happens if your aggregator raises prices, drops an integration, or shuts down? Can you take your configuration elsewhere? Will you have to reconnect every app?
Those questions probably sound familiar. They’re versions of the same ones that got you thinking about AI lock-in in the first place.
An aggregator can make it easier to leave an AI provider while making itself harder to leave. That belongs in the decision too.
Who actually needs one?
If you’re happy with a single AI product and its built-in connections cover your needs, you may have little reason to add an aggregator. There’s no need to add another layer just because you can.
For non-technical consumers who want to use multiple AI products, a hosted aggregator may be a practical choice. Research the provider, think through the access you’re granting, and decide whether the flexibility is worth the additional trust.
For developers and technically experienced users, self-hosting may be worth a look. You get more control over your connections and security choices, as long as you’re willing to handle the maintenance too.
For me, keeping my connections independent has already made switching easier. I want to use whichever AI product works best for me today, and have fewer things to untangle if I change my mind tomorrow.
A few options to explore
These are a few starting points for your own research, rather than a ranked list or blanket recommendation. Check how each fits your apps, AI products, and access requirements.
- Composio: A managed platform for connecting AI products and agents to app integrations, with authentication and tool execution.
- Arcade.dev: A catalog of tools with built-in authentication for connecting AI agents and compatible MCP clients to other services.
- Open Connector (self-hosted): A connector platform for giving AI agents access to app integrations through API, SDK, and MCP. You can run it on your own infrastructure, with your own database and encryption key.