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Ads MCP for Snapchat

Ads MCP for Snapchat

by Usame794
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

snap_funnel

Read-only

Identify funnel drop-off across impressions, swipes, content views, add to cart, checkout and purchases, with step-to-step rates and the weakest step for an account, campaign, ad squad or ad.

Instructions

Where do people drop off? (read-only) Impressions, swipes, content views, add to cart, checkout and purchases with the rate from each step to the next and the weakest step, for the account or one campaign, ad squad or ad over the last 1-31 full local days. Steps your pixel does not send are listed as missing.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "snap_funnel"
  }
}

Input Schema

NameRequiredDescriptionDefault
idNoRequired unless entity is adaccount
daysNo
entityNoadaccount

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already state read-only and open-world behavior, while the description adds useful context beyond them: the funnel stages, step-to-step rates, weakest-step identification, 1-31 full local day window, and that missing pixel steps are listed as missing. It still does not clarify the response shape or aggregation level, which matters without an output schema.

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 opening question front-loads the purpose, and the remaining details are dense but relevant with little wasted wording. The long single sentence is slightly harder to scan than a structured list would be.

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 read-only analytical tool with no output schema, the description covers the funnel metrics, scope, time window, and missing-step behavior well. It leaves some gaps around return structure and id requirements, but those are partially covered by the schema.

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 only 33%, so the description does meaningful compensation by explaining entity scope (account, campaign, ad squad, ad) and the time window as 1-31 full local days. It does not explicitly restate the id requirement for non-account entities, but the schema carries that detail.

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 clearly defines a funnel drop-off analysis and lists the exact stages and derived outputs (step-to-step rate, weakest step). It does not explicitly differentiate itself from sibling analytics tools, so it stops short of a 5.

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

Usage Guidelines3/5

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

Usage is strongly implied by the opening question and by the account/campaign/adsquad/ad scoping, but the description gives no explicit when-to-use or when-not-to-use guidance versus alternatives such as anomaly checks or audience insights.

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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