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IBM watsonx.data MCP Server

Official
by IBM

execute_insert

Insert data into watsonx.data by executing INSERT SQL queries on a specified engine, with required catalog and schema names.

Instructions

Execute INSERT queries against watsonx.data.

Args: sql: SQL INSERT query to execute (must start with INSERT) catalog_name: Target catalog (e.g., "iceberg_data", "hive_data") schema_name: Default schema for unqualified table names engine_id: Engine to run query on (from list_engines, must be running)

Returns: Dict with: - query_id: Unique query identifier - rows_inserted: Number of rows inserted (if available) - execution_time_ms: Query duration in milliseconds - status: Query execution status - catalog_name, schema_name: Echo of inputs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYes
catalog_nameYes
schema_nameYes
engine_idYes

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 carries the full burden. It details the return structure (query_id, rows_inserted, etc.) and constraints (SQL must start with INSERT, engine must be running), but does not mention that INSERT modifies data or any potential side effects.

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 and bullet points, each sentence adding value without redundancy. It is appropriately sized for the tool's complexity.

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 no output schema, the description fully covers return values. All four required parameters are explained, and the tool's role among 39 siblings is clear. The description provides sufficient information for correct invocation.

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?

Schema coverage is 0%, so the description fully compensates by explaining each parameter: sql expects an INSERT query, catalog_name with examples, schema_name as default for unqualified names, and engine_id sourced from list_engines and must be running.

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 it executes INSERT queries against watsonx.data and specifies that the SQL must start with INSERT, distinguishing it from siblings like execute_select or execute_update.

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?

It explains parameters including the requirement that engine_id must come from list_engines and be in a running state. While it doesn't explicitly contrast with alternatives, the 'must start with INSERT' implies the appropriate use case.

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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