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LinkedIn Ads MCP by InsightfulPipe

LinkedIn Ads Setup Helper

query_contexts
Read-only

Helper for planning InsightfulPipe LinkedIn Ads data queries.

Step 1: request='accounts' – Retrieve workspace_id, brand_id, ad_account_id, other source metadata, AND available_actions (all tables you can query).

Step 2: request='actions_details' with actions=['xxxxxx', 'xxxxxx', 'xxxxxx'] – REQUIRED before querying. Replace with actions from available_actions to get the exact request body, required identifiers, fields, time ranges, and notes for each action.

Optional: request='available_actions' – Standalone call to list all available tables/actions (already included in accounts response).

Optional: request='brands' with brand_id + workspace_id to pull brand guidelines.

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": {
      "request": "<request>"
    },
    "name": "query_contexts"
  }
}

Input Schema

NameRequiredDescriptionDefault
actionsNo
requestYes
brand_idNo
platformNo
workspace_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With readOnlyHint=true already declared, the description correctly reinforces a read-only metadata role and adds real content: what each mode returns and the hard rule that actions_details must be called before querying. It omits auth/prerequisite details and any note on rate limits or result size, keeping it short of a 5.

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?

Step-numbered layout is front-loaded and scannable, and the 'already included in accounts response' aside prevents a wasted call. Slightly verbose in repeating the sample actions array syntax, but no sentence is pure filler.

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?

A rich output schema exists, so return-value documentation is unnecessary, and the description covers the sequencing an agent needs. The gaps are the undocumented platform parameter and the absent link to execute_action/query_data, which an agent may still have to discover on its own.

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 0%, so the description must carry parameter meaning. It does well for request (all four enum values explained), actions (must be drawn from available_actions, array shape implied by the example), workspace_id and brand_id (tied to the brands mode), but platform is never mentioned anywhere, leaving one of five parameters undefined in both schema and description.

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 establishes this as a planning/metadata helper and then enumerates each of the four request modes with what each returns (accounts → ids + available_actions; actions_details → request body, identifiers, fields; brands → guidelines). That is more specific than the title, though the description never names the siblings it precedes (execute_action, query_data), so the boundary is implied rather than stated.

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?

It prescribes an explicit ordered workflow (Step 1 accounts, Step 2 actions_details REQUIRED before querying) and labels the remaining modes Optional, even flagging that available_actions is redundant with the accounts response. An agent knows exactly which call to make first and what is a precondition.

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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