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DimiDR

SAP Datasphere MCP Server

by DimiDR

get_relational_metadata

Retrieves relational metadata for an asset, delivering schema details like tables, columns, data types, keys, and relationships for ETL planning. Maps OData types to SQL types.

Instructions

Retrieve CSDL metadata for relational consumption of a specific asset. Returns complete schema information including tables, columns, data types, primary/foreign keys, and relationships for relational data access and ETL planning. Includes SQL type mapping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_idYesAsset identifier (e.g., 'CUSTOMER_VIEW')
space_idYesSpace identifier (e.g., 'SAP_CONTENT')
map_to_sql_typesNoMap OData types to SQL types (default: true)
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It transparently discloses the return content ('complete schema information including tables, columns, data types, primary/foreign keys, and relationships') and the SQL type mapping behavior. It does not mention potential limitations or output format, but for a read-only metadata retrieval tool, the level of disclosure is sufficient.

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 three sentences, front-loaded with the main action, and each sentence adds value: what it does, what it returns, and a key feature. No fluff or redundant phrasing.

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?

With no output schema, the description sufficiently explains what the tool returns (complete schema info, relationships, SQL type mapping). It covers the core need for relational access and ETL planning. However, it could be slightly clearer about how this differs from similar metadata tools, and it doesn't mention any pagination or limit behavior, which might matter for large assets.

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?

The schema description coverage is 100%, so all three parameters are already documented. The description adds no extra meaning beyond what the schema provides; it only mentions SQL type mapping, which is already described in the schema. Baseline 3 is appropriate since the description doesn't need to compensate.

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 function: 'Retrieve CSDL metadata for relational consumption of a specific asset.' It specifies the resource (CSDL metadata for a specific asset) and the purpose (relational consumption), and it lists concrete deliverables (tables, columns, data types, keys, relationships) that distinguish it from siblings like get_analytical_metadata or get_table_schema.

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 description gives context ('for relational data access and ETL planning') which implies when to use it, but it does not explicitly differentiate from closely related siblings like get_relational_entity_metadata or list_relational_entities. There is no explicit 'when not to use' or alternative recommendation, leaving some ambiguity.

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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