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MarioDeFelipe

SAP Datasphere MCP Server

search_catalog

Search across all SAP Datasphere catalog items using advanced syntax. Use scope prefixes and boolean operators to find KPIs, assets, spaces, models, views, and tables.

Instructions

Universal search across all catalog items in SAP Datasphere using advanced search syntax. Supports searching across KPIs, assets, spaces, models, views, and tables. Use SCOPE:<scope_name> prefix for targeted searches. Boolean operators (AND, OR, NOT) supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query with optional SCOPE prefix. Format: 'SCOPE:<scope> <terms>'. Scopes: SearchAll, SearchKPIsAdmin, SearchAssets, SearchSpaces, SearchModels, SearchViews, SearchTables. Example: 'SCOPE:comsapcatalogsearchprivateSearchAll financial'
topNoMaximum number of results to return (default: 50, max: 500)
skipNoNumber of results to skip for pagination (default: 0)
include_countNoInclude total count of matching results (default: false)
include_why_foundNoInclude explanation of why each result matched (default: false)
facetsNoComma-separated list of facets to include or 'all' for all facets. Example: 'objectType,spaceId'
facet_limitNoMaximum number of facet values to return per facet (default: 5)
Behavior2/5

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

No annotations provided, and description does not disclose behavioral aspects like idempotency, side effects, or permissions. It only describes input syntax, not server behavior.

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?

Two succinct sentences: first defines purpose, second adds essential syntax hints. No redundancy or filler.

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

Completeness2/5

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

Does not describe return format, pagination behavior, or how results are structured. Given complex optional parameters and no output schema, more detail is needed for complete understanding.

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

Parameters3/5

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

Schema covers all parameters with descriptions (100% coverage). Description adds minimal extra value (e.g., SCOPE prefix usage), but semantics are mostly captured in schema. Baseline 3 applies.

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 is a universal search across all catalog items and lists specific item types (KPIs, assets, etc.). It distinguishes from sibling tools like search_tables by implying broader scope.

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 using SCOPE prefix and Boolean operators for targeted searches. Lacks explicit when-not-to-use or alternatives, but context is clear enough for an AI agent to decide.

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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