Natural language queries with LLMs via MCP servers

[Tim Jenness]

At the recent SPIE meeting in Copenhagen, Ashley Barnes from ESO gave a
talk on their experiments with teaching an LLM to query their data archive.
They looked at making a dedicated agent taught explicitly but this cost
them real money, and they looked at writing markdown instructions that the
LLM could read to learn about the specifics of the archive center. This led
me to ponder whether we should be talking about some kind of standardized
MCP server interface (
https://modelcontextprotocol.io/docs/getting-started/intro) that an LLM
could query to work things out about the archive.

This seems to be the way that many services are heading (my photos
application has an MCP server to let an LLM look for photos efficiently).
On the one hand we have all these open protocols so that in theory an LLM
can work it all out and form the right query for a TAP server by querying
registry and looking at TAP_SCHEMA, and that should work. MCP *might* be
able to let an agent do the same thing but using fewer tokens, even if the
end point is the agent sending off a TAP query.

Is anyone else thinking about this? Can someone from ESO ask Ashley to join
IVOA Slack to discuss this?

Each data center could put their own MCP server up with their own targeted
API and that might be fine, but pooling our experience in terms of what
helped and what made things worse would be really helpful and if we end up
with an IVOA Note containing advice on natural language queries that would
be great. If we ended up with a standardized vocabulary for MCP servers
that might be even better.

-- 
Tim Jenness
Rubin Observatory
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.ivoa.net/pipermail/interop/attachments/20260727/7067df9b/attachment.htm>