lu-query

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create_mview_log

Create a materialized-view log on an Oracle master table to enable fast refresh and DML tracking for materialized views.

Instructions

Create a materialized-view log on a table for fast refresh. Requires CREATE TABLE privilege and tablespace quota; Oracle returns ORA-01031 / ORA-01950 otherwise.

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": {
      "table": "<table>"
    },
    "name": "create_mview_log"
  }
}

Input Schema

Name	Required	Description
`table`	Yes	Master table name.
`schema`	No	Schema (owner) of the master table. Optional — defaults to the server's current schema; omit rather than guess.
`withRowid`	No	Whether to include ROWID columns.
`withPrimaryKey`	No	Whether to include PRIMARY KEY columns (recommended).
`includingNewValues`	No	Whether to add INCLUDING NEW VALUES (enables fast refresh with DML tracking).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.16.3Oct 18, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does add real value: it discloses required privileges (CREATE TABLE, tablespace quota) and the concrete failure modes (ORA-01031 / ORA-01950), which an agent could not infer from the schema. It stops short of covering idempotency or what happens if a log already exists.

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?

Two sentences, no filler, and the core action is front-loaded ahead of the prerequisite/error detail. Every clause earns its place.

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?

For a DDL tool with no annotations and no output schema, the description covers purpose, prerequisites, and error conditions adequately. Minor gaps remain around duplicate-log behavior and return value, but the essentials for a correct call are present.

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 the schema already documents all five parameters including the schema default and the withPrimaryKey recommendation. The description adds no parameter-level meaning beyond that, so baseline 3 applies.

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?

States a specific verb (Create), resource (materialized-view log), and target (on a table), plus the reason (for fast refresh). An agent can distinguish it from read-side siblings like list_mview_logs and from other create_* tools without opening the 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 phrase 'for fast refresh' implies the scenario in which this DDL is warranted, which is useful context. However, it names no alternatives and gives no explicit when-not guidance (e.g., how it relates to creating the materialized view itself, or to list_mview_logs). Usage is implied rather than stated.

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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