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monsterygy

Oracle Database MCP Server

by monsterygy

Update records

db_update
Destructive

Update records in an Oracle database table using parameterized named binds. Enforces a WHERE clause and limits affected rows to prevent accidental mass updates.

Instructions

Update one or more records in an Oracle database table using parameterized named binds.

Auto-generates the SET clause from the data object. The WHERE clause MUST include named bind variables (:w_1, :w_2, ...) with corresponding where_params.

Safety features:

  • WHERE clause is REQUIRED (updates without conditions are blocked)

  • Pre-counts matching rows and refuses if exceeding DML_MAX_ROWS (default: 1000)

  • dry_run mode previews SQL + affected row count

Example: table_name: "users" data: { "status": "active" } where: "id = :w_1" where_params: [42] dry_run: false

Args:

  • table_name, data, where, where_params, dry_run (default: false)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesColumn-value pairs to SET. Example: {"status": "active"}
whereYesWHERE clause with named bind variables (:w_1, :w_2, ...). Example: 'id = :w_1 AND status = :w_2'
dry_runNoIf true, return the generated SQL and affected row count without executing.
table_nameYesTarget table name
where_paramsYesValues for :w_1, :w_2, ... in order. Example: [42, 'inactive']
Behavior5/5

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

Discloses key behaviors: mandatory WHERE clause, DML_MAX_ROWS check, dry_run mode. These add context beyond annotations (destructiveHint=true, readOnlyHint=false). No contradictions.

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?

Well-structured with bullet points and example, but could be slightly more concise. Every sentence adds value.

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?

No output schema, but description covers return behavior for dry_run. Safety features and defaults are clearly documented. Complete for a mutation tool.

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

Parameters4/5

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

Schema coverage is 100%; description adds value by explaining auto-generated SET clause and naming convention for where_params, enhancing understanding.

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 updates records in an Oracle database using parameterized named binds. It distinguishes from siblings like db_insert and db_delete.

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?

Provides clear guidance on required WHERE clause and safety limits, but does not explicitly contrast with other tools or provide when-not-to-use scenarios.

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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