MCP OpsBridge

db_insert_row

Insert a new row into a database table by providing the table name and column-value pairs. The operation is auto-approved and logged for audit.

Instructions

Insert a new row into a table (auto-approved, logged)

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>",
      "data": "<data>"
    },
    "name": "db_insert_row"
  }
}

Input Schema

Name	Required	Description	Default
`data`	Yes	Column-value pairs to insert
`table`	Yes	Table name to insert into

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Aug 10, 2026

TDQS

A3.5/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It adds useful context with 'auto-approved' (no approval needed) and 'logged' (audit trail). However, it omits mutation side-effects, return behavior, error conditions, or prerequisites, leaving gaps for a write operation.

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 a single, front-loaded sentence that clearly states the action and resource. The parenthetical 'auto-approved, logged' adds valuable behavioral context without unnecessary length. Every word contributes.

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

Completeness3/5

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

For a 2-parameter insert tool with full schema coverage, the description is minimally sufficient. It explains the operation and adds two behavioral properties. However, it does not cover return values, failure modes, or when to choose this over other DB tools, which leaves some gaps for a mutation tool with no annotations or output schema.

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%, with 'table' and 'data' both described. The description adds no extra parameter-level meaning beyond what the schema already provides. Since the schema handles the heavy lifting, a baseline score of 3 is appropriate.

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 uses a specific verb and resource: 'Insert a new row into a table'. This clearly distinguishes the tool from sibling tools like db_update_rows, db_delete_rows, and db_execute_query. The core purpose is unambiguous.

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 does not state when to use this tool versus alternatives such as db_execute_query or db_update_rows. The only hint is 'auto-approved, logged,' which addresses workflow but not selection criteria. While the name implies insertion, explicit usage guidance is missing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.