Hey, good question. Marmot is designed to be as generic as possible. An "Asset", whether it's a database, glossary term, topic, API or anything else, has the exact same schema, API endpoint and MCP tool. The MCP server exposes 3 tools: discover_data, find_ownership and lookup_term. Scoping happens as filters and arguments to discover_data, and it's summary-first, so a broad query returns counts or provider breakdowns rather than dumping every asset into context, and the agent narrows from there. The search step is really the primary interface here.

Makes sense. 3 generic tools + summarize first is a nice approach to sidestepping the problem of too many tools. But it looks like it shifts the chokepoint around rather than eliminating it: instead of "choose the proper tool out of many", it shifts to "formulate the appropriate query to discover_data from the summary".

But in real applications, does the model reliably drill down from the general summary, or does it often just hang around at the level of the summary?