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IBM watsonx.data MCP Server

Official
by IBM

create_spark_engine

Create a Spark engine in IBM watsonx.data to process data with configurable origin, storage, and catalogs.

Instructions

Create a new Spark engine in watsonx.data.

Args: origin: Engine origin - "native", "external", or "discover" display_name: Display name for the engine storage_name: Storage/bucket name for engine_home (REQUIRED) associated_catalogs: List of catalog IDs to associate description: Engine description default_version: Spark version (default: "3.5") default_config: Additional engine configuration tags: Tags for the engine

Returns: Dict with created engine details including engine_id

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originYes
display_nameYes
storage_nameYes
associated_catalogsNo
descriptionNo
default_versionNo3.5
default_configNo
tagsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It describes creation and return type but lacks details on side effects, authorization requirements, or consequences. Basic but not comprehensive.

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?

The description is structured with Args and Returns, front-loaded with the purpose sentence. It is clear but not overly concise; each sentence adds information.

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

Completeness2/5

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

Given 8 parameters and no annotations, the description covers basics but lacks prerequisites, error conditions, or dependencies. An output schema exists but does not fully compensate for missing context.

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 0%, so description must add meaning. It provides brief descriptions for each parameter (e.g., origin values), adding value beyond the schema. However, some descriptions are obvious (e.g., display_name).

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 Spark engine in watsonx.data.' It uses a specific verb ('create') and resource ('Spark engine'), and distinguishes it from sibling tools like create_presto_engine.

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

Usage Guidelines2/5

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

The description lists parameters including origin types but gives no guidance on when to use this tool versus alternatives like create_presto_engine or when not to use it. No explicit when-to-use or when-not-to-use information.

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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