SAS MCP Server

Official

by sassoftware

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Python

Remote

Catalog Search

catalog_search

Read-onlyIdempotent

Locate SAS assets (tables, columns, reports) across Viya without knowing server/library. Query by name, type, metadata facets, or date range; use the returned resource URI to act on the live asset.

Instructions

Search the SAS Information Catalog for assets (tables, columns, reports, ...).

The catalog is a metadata index across the whole Viya environment, so this finds assets without needing to know their server/library first. Each hit includes the asset's resource_uri — the URI you can hand to the matching tool (e.g. get_report, get_castable_data) to act on the live asset — and an attributes map with whatever metadata the catalog holds for it (commonly library, rowCount, columnCount, completenessPercent, reviewStatus, informationPrivacy, and analysisTimeStamp).

The query uses the SAS catalog search grammar:

Free text matches names, with wildcards * (0+ chars) and ? (1 char): cust*.
Facets constrain fields, e.g. AssetType:Report, Name:sales, Library.name:PUBLIC, Column.informationPrivacy:Sensitive.
Ranges DateModified:[2024-01-01 TO 2024-12-31] and + to require a term. Combine freely: AssetType:"CAS Table" +Name:cust*. Use catalog_search_helper to discover valid facet names and values.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum hits to return (default 20).
`query`	Yes	The catalog search query (see grammar above). Use ``*`` to match all names.
`start`	No	Offset of the first hit (default 0).
`indices`	No	Comma-separated index name(s) to search (default 'catalog').	catalog

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.2.1Jul 4, 2026

TDQS

A4.7/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Even with annotations declaring readOnlyHint, idempotentHint, and destructiveHint, the description adds substantial behavioral context: it explains that each hit includes a resource_uri and an attributes map with common metadata keys, and it details the catalog search grammar with examples. This goes well beyond the structured annotations and tells the agent what to expect from results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every section earns its place: a one-sentence purpose, a return-value explanation, and a compact bulleted grammar guide with concrete examples. It is front-loaded with the most important scoping information and ends with a practical pointer to catalog_search_helper, with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with a non-trivial query grammar, the description is complete: it explains when to use it, what results look like, how to interpret resource_uri, and how to learn valid facets. The output schema is reportedly present, and the description covers the return shape anyway, so an agent has everything needed to call and consume the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters like limit, start, and indices are already documented. The description adds significant meaning for the query parameter by specifying the search grammar, wildcards, facets, ranges, and combination syntax, which is essential for correct invocation. This raises it above the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Search the SAS Information Catalog for assets') and immediately distinguishes itself from siblings by explaining it is a metadata index across the whole Viya environment that finds assets without knowing the server/library first. It also clarifies how results connect to other tools via resource_uri, making the tool's role in the ecosystem unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use this tool: when you need to find assets without knowing their server or library, or when you want to discover assets by name, facets, or ranges. It also points to catalog_search_helper for discovering valid facet names and values. It does not explicitly state when not to use it versus list_* tools, but the 'whole Viya environment' distinction implies the boundary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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