Skip to main content
Glama
MarioDeFelipe

SAP Datasphere MCP Server

by MarioDeFelipe
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

get_asset_details

Get comprehensive metadata for a SAP Datasphere asset including dimensions, measures, relationships, and consumption URLs to understand its structure and access data.

Instructions

Get comprehensive metadata for a specific SAP Datasphere asset.

Use this tool when:

  • User asks "Show me details about the Financial Transactions asset"

  • Need complete asset documentation and structure

  • Want to understand asset dimensions, measures, and relationships

  • Looking for consumption URLs to access the data

  • Checking asset business purpose and technical details

  • Validating asset availability before integration

What you'll get:

  • Complete asset metadata (name, description, business purpose)

  • Space information and ownership details

  • Asset type and consumption type (analytical/relational)

  • Consumption URLs for data access

  • Metadata URLs for schema information

  • Dimensions and measures (for analytical models)

  • Relationships to other assets

  • Technical details (row count, size, refresh info)

  • Business context (domain, classification, retention)

  • Version and status information

  • Tags and categorization

Required parameters:

  • space_id: The space containing the asset (e.g., 'SAP_CONTENT')

  • asset_id: The asset identifier (e.g., 'SAP_SC_FI_AM_FINTRANSACTIONS')

Optional parameters:

  • expand_fields: Related entities to expand (e.g., ['columns', 'relationships'])

Example queries:

  • "Get details for SAP_SC_FI_AM_FINTRANSACTIONS in SAP_CONTENT"

  • "Show me the structure of the Financial Transactions asset"

  • "What are the dimensions and measures of this analytical model?"

  • "Give me the consumption URL for the Sales Data View"

Use cases:

  • Understand asset structure before querying

  • Get consumption URLs for data access

  • Review asset business purpose and classification

  • Check asset relationships and dependencies

  • Validate data freshness (last refresh time)

  • Generate asset documentation

Note: This uses the Catalog API: GET /api/v1/datasphere/consumption/catalog/spaces('{spaceId}')/assets('{assetId}')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
space_idYesThe space ID in UPPERCASE format (e.g., 'SAP_CONTENT', 'SALES_ANALYTICS'). Must match exactly.
asset_idYesThe asset identifier (e.g., 'SAP_SC_FI_AM_FINTRANSACTIONS', 'CUSTOMER_VIEW').
expand_fieldsNoRelated entities to expand (e.g., ['columns', 'relationships', 'metadata']).

Tool Definition Quality

A4.1/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It mentions the API endpoint and return data fields, but does not explicitly state read-only nature or discuss side effects, auth needs, or rate limits. Adequate but could be more explicit.

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

Conciseness4/5

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

Well-structured with sections, bullet lists, and examples. Each section adds value, though the length is slightly above necessary. Front-loaded with purpose.

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

Completeness4/5

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

No output schema, but the description comprehensively lists what metadata will be returned, covers params, examples, use cases, and API details. Lacks error conditions but adequate for the tool's complexity.

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% with descriptions. The description adds value with examples, format hints (UPPERCASE for space_id), and explanation of optional expand_fields, enhancing 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 the verb 'Get' and resource 'comprehensive metadata for a specific SAP Datasphere asset.' It distinguishes from siblings like get_space_assets (list) and get_analytical_model (specific model type).

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 explicit 'Use this tool when:' with examples, 'What you'll get', 'Use cases', and example queries. Does not state when NOT to use or name alternatives explicitly, but context is clear.

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/MarioDeFelipe/sap-datasphere-mcp'

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