you can give it any context you have, worst case in text form, and the llm will try to figure it out, call different endpoints etc. Recently someone mentioned to me the intern test by Hamel Husain: if avg college student can suceed with the given input (with a lot of trying and time), then llms should be able to do it too. So that's the bar we're aiming for.

No api at all is out of scope for now, there are other tools that are better suited for that.

Yes, it does update and cache changed schema for the target API. At runtime. The way it works that every time you make a call to superglue, we get the data from the source and apply the jsonata (that's very fast). We then validate the result against the json schema that you gave us. If it doesn't match, e.g. because the source changed or a required field is missing, we rerun the jsonata generation and try to fix it.

I guess you could regularly run the api just to make sure the mapping is still up to date and there are no delays when you actually need the data, depending on how often the api changes.

Thanks for sharing! We're taking a bit of a different angle here. The APIs we are looking at are not the ones that websites are using, but rather then ones you would typically integrate with when thinking about data integrations. Also, while you could use superglue as an MCP server, the usecases we see right now are less in the AI / agent world but rather in the workflow / ETL / onboarding world.

That being said, the mitmproxy2swagger approach is really really cool as an alternative to mindless scraping.

And with MCP, the idea is that the agent can translate a natural language instruction into the specific API request and then translate the schema into whatever structured output format you want? Is there anything that Superglue does that you wouldn't get somewhat out of the box using agents and MCP? I'm not too familiar with MCP so still trying to understand how it compares to this sort of thing.

> Once you have the OpenAPI specs, you can build an MCP server on top of that. Automatically.

What's the route to doing this automatically? Is there some tool for doing this?

If you're self-hosting, you can bring your own model and there are no limitiations. For the hosted version, we currently do custom pricing agreements with our customers using this in prod, and keep it free for hobbyists within fair use limits. We still need to figure out what the boundaries will be, tbh.

On your open source question, we accept contributions from non-team-members and have done so in the past, particularly on bugs or new features on the backend.

Thanks! The primary reason is because we want folks to be able to run this locally and contribute to the project / fix issues as they come up. This is much harder when you have a black box tool and rely on our small team for support.

Alarm? What about self-healing. That would be neato.

working on it... ping me if you have a usecase in mind and I can set it up for you.

Sure! We use structured output for the endpoint, but not for the jsonata since it's hard to actually describe as a format. 3 big levers for accuracy / reducing hallucinations: 1. direct validation: we apply the jsonata that is generated and check if it really produces what we want (we have the schema after all). This way we can catch errors as they come up. 2. using a reasoning model: by switching to o3-mini, we were able to drastically improve the correctness of the jsonata. takes a bit longer, but better waiting a bit than incorrect mappings. 3. using a confidence score: still in development, but sometimes there are multiple options to map something (e.g. 3 types of prices in the source, but you only want one. Which one?). So we're working on showing the user how "certain" we are that a mapping is correct.

have you looked at Browser Use? https://browser-use.com/

huh interesting. we're exploring extraction from html

Sure, email me: stefan@superglue.cloud

depends on your usecase: - this abstracts away a lot of the complexity, including pagination and format conversion. Also integrated logging and schema validation. - this is self-healing, so when data comes through that you have never seen before or if the api changes it is a lot less likely to break. - if you need to integrate a lot of APIs, or if you have multiple apps needing access to these apis, it is much easier to set up here than writing 1000s of lines of integration code. If none of this is important / applies to you and the generated code works well, then you could also just do that.

because it's easier :) , see: https://news.ycombinator.com/item?id=9224

Thanks!

Thanks for flagging this. Odd. Did this happen on the website or in the actual app? Might be a server overload looking at our logs.

thank you!

not that we're aware of!

thank you!

we're not affiliated

ooof, I assumed this was the same company.