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MarioDeFelipe

SAP Datasphere MCP Server

create_database_user

Create a database user in a SAP Datasphere space with defined consumption and ingestion permissions, returning auto-generated credentials.

Instructions

Create a new database user in a SAP Datasphere space with specified permissions.

IMPORTANT: This is a HIGH-RISK tool that requires user consent before execution.

Use this tool when:

  • User requests "Create a database user named JEFF in SALES"

  • Setting up new user access for applications or analysts

  • Configuring data ingestion users

  • Establishing read-only consumption users

Required parameters:

  • space_id: The space where user will be created

  • database_user_id: User name suffix (e.g., 'JEFF', 'REPORTING_USER')

  • user_definition: JSON object defining permissions and settings

User definition structure:

{
  "consumption": {
    "consumptionWithGrant": false,
    "spaceSchemaAccess": false,
    "scriptServerAccess": false,
    "enablePasswordPolicy": false,
    "localSchemaAccess": false,
    "hdiGrantorForCupsAccess": false
  },
  "ingestion": {
    "auditing": {
      "dppRead": {
        "isAuditPolicyActive": false,
        "retentionPeriod": 7
      },
      "dppChange": {
        "isAuditPolicyActive": false,
        "retentionPeriod": 7
      }
    }
  }
}

Permission types:

  • Consumption: Read access to space data

    • consumptionWithGrant: Allow granting privileges to others

    • spaceSchemaAccess: Access to space schema objects

    • scriptServerAccess: Execute stored procedures/UDFs

  • Ingestion: Write access for data loading

    • Audit policies for compliance (DPP read/change tracking)

Security notes:

  • New password is auto-generated and returned (store securely!)

  • Audit retention period: 1-365 days

  • Minimum privilege principle recommended

  • Password must be changed on first login

Example queries:

  • "Create a read-only database user named ANALYST in SALES"

  • "Set up a database user for data loading in FINANCE"

  • "Create user REPORTING with consumption access"

Note: Corresponds to CLI: datasphere dbusers create --space --databaseuser --file-path <def.json>

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
space_idYesThe space ID where user will be created (e.g., 'SALES', 'FINANCE'). Must be uppercase.
database_user_idYesDatabase user name suffix (e.g., 'JEFF', 'ANALYST', 'ETL_USER'). Will be prefixed with space name.
user_definitionYesJSON object defining user permissions and settings. Must include 'consumption' and 'ingestion' sections.
output_fileNoOptional: Path to save user credentials JSON (e.g., 'jeff.json'). RECOMMENDED for security - credentials shown only once!
Behavior5/5

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

With no annotations provided, the description carries full burden and excels. It discloses that the tool is high-risk, requires user consent, auto-generates a password, and includes security notes (minimum privilege, audit retention). It also hints at the one-time nature of credential display.

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 well-structured with sections, bullet points, and code blocks. It front-loads the critical risk warning and example usage. Every sentence adds value—no filler. Despite length, it remains scannable and organized.

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

Completeness5/5

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

Given the complexity (nested user_definition, high-risk, no output schema), the description is highly complete. It covers required parameters, JSON structure, security implications, and even includes CLI mapping. It leaves no ambiguity for an agent to misuse the tool.

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

Parameters5/5

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

The input schema has 100% description coverage, but the description adds significant value: it explains the user_definition structure in detail, provides example JSON, clarifies that database_user_id will be prefixed with space name, and recommends the optional output_file for security. This goes well beyond the 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 'Create a new database user' and specifies the scope (in a SAP Datasphere space with permissions). It distinguishes from sibling tools like delete_database_user, reset_database_user_password, and update_database_user by focusing on creation. The provided example queries further clarify the purpose.

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

Usage Guidelines5/5

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

The description explicitly lists when to use the tool (e.g., user requests create, setting up user access) and provides example queries. It does not explicitly state when not to use, but the contextual examples implicitly guide against misuse. The high-risk warning also sets expectations.

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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