MCP OpsBridge

approve_action

Approve or deny a pending action that requires user approval. Submit the approval ID and your decision to respond to pending approval requests.

Instructions

Confirm or deny a pending action that requires user approval. Use this to respond to pending_approval or pending_approval_2 responses.

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": {
      "approval_id": "<approval_id>",
      "decision": "<decision>"
    },
    "name": "approve_action"
  }
}

Input Schema

Name	Required	Description
`reason`	No	Optional note explaining why the action was denied
`decision`	Yes	Confirm or deny the pending action
`approval_id`	Yes	The ID from the pending approval request

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Aug 10, 2026

TDQS

A4/5.0

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. It discloses the core behavior (confirm/deny) and the triggering response types, but does not mention side effects, permissions, or return format. This is a minimum viable level of transparency for a mutation tool.

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 two sentences with no wasted words. It front-loads the action and includes a practical usage hint, achieving high conciseness.

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 simple tool with three parameters and no output schema, the description covers purpose and usage context. It does not explain return values or consequences, but the tool is straightforward enough that this is a minor gap.

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 100% with parameter descriptions. The description adds a small amount of context for approval_id by mentioning the response types, but overall it does not significantly enhance understanding beyond the schema. Baseline 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 ('Confirm or deny') with a clear resource ('pending action that requires user approval'), and it explicitly names the response types ('pending_approval or pending_approval_2 responses') it responds to, making it easy to distinguish from sibling tools.

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?

The description provides clear context for when to use the tool ('Use this to respond to pending_approval or pending_approval_2 responses'). It does not explicitly list exclusions or alternatives, but given the sibling tools, none directly compete, so the guidance is sufficient.

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