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SAP Datasphere MCP Server

SAP Datasphere MCP Server

by DimiDR
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_relational_entities

List tables and views in an SAP Datasphere asset, returning OData entity sets for data extraction and ETL processes.

Instructions

List all available relational entities (tables/views) within a specific SAP Datasphere asset for row-level data access and ETL operations. Returns OData entity sets that can be queried for detailed data extraction.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "space_id": "<space_id>",
      "asset_id": "<asset_id>"
    },
    "name": "list_relational_entities"
  }
}

Input Schema

NameRequiredDescriptionDefault
topNoMaximum number of entities to return (default: 50, max: 1000)
asset_idYesAsset identifier (e.g., 'SAP_SC_FI_AM_FINTRANSACTIONS')
space_idYesSpace identifier (e.g., 'SAP_CONTENT')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A3.5/5.0
Behavior2/5

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

With no annotations, the description carries the full burden, but it only says 'Returns OData entity sets' without stating that the operation is read-only, requires specific permissions, or has side effects. It does not disclose pagination behavior or other limitations beyond the schema's top parameter, leaving significant ambiguity about execution 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?

The description is two sentences, front-loaded with the main verb and resource, and contains no redundant wording. It efficiently communicates purpose and return type.

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

Completeness3/5

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

For a simple listing tool, the description covers the core action and return type, but without annotations or an output schema it leaves gaps: what exactly an 'OData entity set' contains is unspecified, and pagination is only hinted at via the top parameter. It is adequate but not rich.

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 coverage is 100%, so space_id, asset_id, and top are already fully documented with examples and defaults. The description adds no additional parameter-specific meaning, only a general reference to 'a specific SAP Datasphere asset' that loosely maps to the required parameters.

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 action: 'List all available relational entities (tables/views) within a specific SAP Datasphere asset.' It also clarifies the return type ('Returns OData entity sets') and distinguishes the tool from query or metadata tools by focusing on enumeration.

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

Usage Guidelines3/5

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

The phrase 'within a specific SAP Datasphere asset for row-level data access and ETL operations' gives context on when the tool is useful, but it does not explicitly contrast with sibling tools like query_relational_entity or get_relational_entity_metadata. Usage guidance remains implicit rather than direct.

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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