source-and-search.md

title	Source and Search Tools
sidebar_position	3

Source and Search Tools

Use these tools at the start of an agent workflow to load a model, find relevant ontology objects, and resolve business labels.

load_ontology

Compiles one or more SemLang files or inline source strings and stores the resulting model in the MCP session.

Inputs

Field	Type	Notes
path	string	Explicit SemLang file path escape hatch. Normal projects should use .semlang/settings.yml and omit this.
source	string	Inline SemLang source.
malloyConfigPath	string	Explicit Malloy config file escape hatch. Normal projects should use .semlang/settings.yml.
returnMalloyModel	boolean	When true, include the full compiled Malloy model in malloyModel. Defaults to false.

With no inputs, load_ontology uses the entrypoint and runtime paths from .semlang/settings.yml. If no config is available, it returns setup guidance instead of guessing paths.

Output

Returns ok, diagnostics, and a context summary with package name, loaded files, counts, source names, type names, concept names, lens names, query names, and Malloy project/config context when available. The full compiled Malloy model is omitted by default and returned as malloyModel only when requested with returnMalloyModel.

Example

{}

search

Searches concepts, metrics, members, queries, and lenses using terms from a user question or phrase. It can also resolve ontology names or business labels when kind is entity.

Inputs

Field	Type	Notes
query	string	Search text, ontology name, or business label.
kind	string	Optional result kind: any, concept, member, metric, lens, query, or entity.
limit	number	Maximum results per category. Defaults to 20.

Output

Metadata search returns matching concepts, metrics, members, queries, lenses, actions, and roles. Each match includes a score and matched terms. Entity resolution returns matching sources, types, concepts, members, lenses, queries, candidate identifiers, candidate fields, matching rows when local DuckDB example data is available, and roles.

Lens-oriented responses include scored lenses with descriptions, parents, refined concepts, scores, and matched terms. Use find_paths when the exact join route matters.

Example

{
  "query": "monthly margin and returns by region and product category",
  "limit": 8
}

Example

{
  "kind": "entity",
  "query": "Store Denver"
}