Ask HN: How are people building SaaS integrations for AI agents?
gist.github.com
gist.github.com
However, all open source integration repositories are filled with custom code. Each repository choosing how to code in their own format and structure for authentication, api configuration and several of them mapping to their own formats. Not seen a single one of them actually use the OpenAPI Specification (OAS) to create their repository of integrations. You cannot really convert OAS to custom code specific to your application and vice versa.
Some of the Open Source Integration repos I have looked at: cptn.io, windmill, cloudquery, airbyte, revert, n8n, active pieces, singer, rudderlabs, handshake(only for oauth.
I believe AI systems and companies in general looking to work with integrations would really benefit from configuration objects that define how to use the apis of all saas platforms, especially those that do not have the OAS.
Would an open source standard to define Oauth (like the gist link) be useful? Furthermore a configuration object and parser that can be reproducible from OAS to be used in interacting with saas apis? Lastly an open source mapper (based on jsonata) to seamlessly convert one schema to another.
We have heard the opposite argument for AI agents: The people we spoke with want control over what the AI agents can do in the external systems. With direct API access and non-deterministic behavior, how do you guarantee it doesn't swap the POST /contacts with DELETE /contacts?
Integration platforms that abstract the API provide a safety net for this, and auditability.
Reason I did not include you in the open source list is your github only seems to have "integration templates". I may be wrong but these look like helpers for your customers to understand your integration formats. All your integrations do not seem to actually be open sourced. Especially
I agree that AI agents can always misunderstand and call the wrong api. Thus I believe having an open source configuration standard, interoperable with OAS, which AI agents can parse would be hugely beneficial. Audibility of course is also definitely crucial with any AI system.
The fundamental issue I see with API abstraction over the core system is the inability to fully interact with the underlying system for bespoke requests that may come up. Also the issue with the AI systems calling the wrong api (POST instead of DELETE), can still arise with any system an AI interacts with tho I agree that besides securing with appropriate oauth scopes, integration platforms could help with additional guard rails