Skip to main content
Glama
Sign In

OpenAI Ads MCP by InsightfulPipe

by com.insightfulpipe
OverviewDiscussionsAdmin

OpenAI Ads Execute Action

execute_action
Destructive

Execute OpenAI Ads action (Step 3 (FINAL) of workflow).

REQUIRED: Complete these steps first using query_contexts:

  1. request='accounts' - Get workspace_id, brand_id, ad_account_id AND available_actions

  2. request='actions_details' with actions=['xxxxxx', 'xxxxxx', 'xxxxxx'] - Get detailed body structure for specific action(s) using actions from available_actions

IMPORTANT: Always call step 2 to see the exact body structure before executing.

Rely on info from steps 1-2 to construct the action body. Follow the schema exactly.

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": {
      "body": "<body>"
    },
    "name": "execute_action"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=true, and openWorldHint=true, so the safety profile is covered. The description adds useful procedural context about getting the exact body structure first, but it does not explain what the action changes, whether effects are reversible, or what permissions are required.

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?

The description is front-loaded with the workflow context and uses clear step labels. It is slightly repetitive with the repeated emphasis on calling step 2 and the placeholder action list, but most sentences carry useful procedural information.

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?

Given the existence of an output schema and rich annotations covering destructive/open-world behavior, the description provides enough workflow context to call the tool correctly. Body field details are appropriately deferred to query_contexts, though it could say more about side effects or permission requirements.

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 description coverage is 0% for the single body parameter, so the description must compensate. It does so by instructing the agent to construct the body from steps 1–2, retrieve detailed body structure via actions_details, and follow the schema exactly, which meaningfully guides use of a dynamic body parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource, “Execute OpenAI Ads action,” and identifies it as the final workflow step, which distinguishes it from the sibling query_contexts. However, “action” is generic and the exact action types are deferred to available_actions from step 1, so purpose is clear but not fully concrete.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit mandatory prerequisites: call query_contexts with request='accounts', then request='actions_details' with specific actions, and always call step 2 before executing. It clearly routes the agent through the workflow and makes the sequencing non-optional.

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

All OpenAI Ads MCP by InsightfulPipe toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources