Skip to main content
Glama
sassoftware

SAS MCP Server

Official
by sassoftware

catalog_run_adhoc_analysis

Submit an ad-hoc analysis job to profile a catalog table, computing column statistics, data dictionary, and data-quality metrics. Optionally enable NLP for semantic enrichment of privacy and keyword signals.

Instructions

Submit an ad-hoc analysis (profiling) job for a table in the catalog.

Profiles the table — computing the data dictionary, column statistics, and data-quality metrics that catalog_download_table_profile returns. The job runs asynchronously and may take a while; poll catalog_get_adhoc_analysis with the returned job id until the profile is ready.

The three NLP job parameters are enabled by default — they drive the semantic enrichment that populates an asset's informationPrivacy, nlpTerms, nlpTags, and mostImportantFields (the privacy and keyword signals the catalog is most useful for). Leave them on unless you only need a plain column profile and want the job to finish faster.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesA name for the analysis job.
providerNoJob provider (default 'TABLE-BOT').TABLE-BOT
descriptionNoOptional description for the job.
resource_uriYesSource URI of the table to analyze (the ``resource_uri`` from a catalog_search hit, e.g. '/dataTables/dataSources/cas~fs~.../tables/MYTABLE').
resource_typeNoCatalog entity type of the resource. Defaults to 'CASMEMTable' when the URI is a CAS table (contains 'cas~fs~'); pass it explicitly for other asset types.
analyze_sentimentNoScore sentiment on text columns (default True).
identify_languageNoDetect each text column's language (default True).
get_nlp_semantic_idNoDerive semantic types / privacy classification (informationPrivacy, nlpTerms, nlpTags) (default True).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Without annotations, the description fully discloses async behavior, need to poll, and effect of NLP parameters on output (enriching privacy and keyword signals). No contradictions.

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?

Concise yet comprehensive: two paragraphs front-loading purpose, then explanation of async nature and parameter guidance. Every sentence adds value, no redundancy.

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?

Covers the entire workflow: what the tool does, how results are obtained (polling), parameter details, and the optional trade-off for NLP. Suitable for correct invocation despite missing annotations.

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?

With 100% schema coverage, baseline is 3. The description adds context about the three NLP parameters driving semantic enrichment and affecting job speed, and explains resource_uri comes from catalog_search hits, adding value beyond schema.

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 clearly states it submits an ad-hoc profiling job for a catalog table, computing data dictionary, column statistics, and data-quality metrics. It explicitly mentions that the results are what catalog_download_table_profile returns, distinguishing it from that sibling.

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?

Provides guidance on when to use (when you need profiling) and gives advice on NLP parameters (leave on unless plain profile needed and faster job desired). Mentions polling with catalog_get_adhoc_analysis. Absence of explicit 'when not to use' or alternative tool comparisons beyond catalog_download_table_profile.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sassoftware/sas-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server