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SAP Datasphere MCP Server

SAP Datasphere MCP Server

by DimiDR
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_object_definition

Retrieve detailed SAP Datasphere object definitions, including columns, keys, SQL, transformations, and metadata. Understand implementation details, extract schemas, or plan migrations.

Instructions

Get complete design-time object definition from SAP Datasphere repository. Retrieves detailed structure, logic, transformations, and metadata for tables (with columns, keys, indexes), views (with SQL definitions), analytical models (with dimensions/measures), and data flows (with transformation steps). Use this for understanding object implementation details, extracting schema information, or planning migrations.

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>",
      "object_id": "<object_id>"
    },
    "name": "get_object_definition"
  }
}

Input Schema

NameRequiredDescriptionDefault
space_idYesSpace identifier (e.g., 'SAP_CONTENT')
object_idYesObject identifier/name (e.g., 'FINANCIAL_TRANSACTIONS', 'CUSTOMER_VIEW')
include_dependenciesNoInclude dependency information (upstream sources and downstream consumers)
include_full_definitionNoInclude complete object definition with all details (columns, transformations, logic)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description must carry the burden of disclosing behavior. It clearly indicates a read-only 'get' operation and details what content is retrieved (columns, keys, SQL, dimensions, transformations). While it doesn't mention permissions or side effects, the read-only nature is implied by the verb 'Get' and the listed return content.

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 concise and well-structured: two sentences that front-load the core purpose and then provide additional detail on object types and use cases. Every sentence adds value without waste.

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?

Given the tool's complexity and lack of an output schema, the description provides helpful context by listing what is returned for each object type. It also differentiates from sibling tools by covering multiple object types, though it doesn't specify response structure or pagination. This is reasonably complete for a retrieval tool.

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 description coverage is 100%, so all four parameters are already documented in the schema. The description does not add any additional parameter-specific semantics beyond what the schema provides, which aligns with the baseline score of 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 clearly states the tool's purpose with a specific verb ('Get') and resource ('complete design-time object definition from SAP Datasphere repository'). It enumerates specific object types (tables, views, analytical models, data flows) and their content, which differentiates it from siblings like get_table_schema or get_asset_details.

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 provides explicit use cases: 'understanding object implementation details, extracting schema information, or planning migrations.' This gives clear context for when to use the tool, though it does not explicitly mention when to prefer alternatives like get_table_schema or get_analytical_model.

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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