Facebook Ad Library MCP

Transcribe a video ad

transcribe_ad

Read-onlyIdempotent

Convert a video ad's spoken audio into readable text using its Ad Library ID. If the backend can't do this, it explains why instead of failing silently.

Instructions

Speech to text for a video ad, so its spoken script becomes readable. Only the scrapecreators backend can do this. On any other backend it explains that rather than failing silently.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`library_id`	Yes	The Ad Library ID of a video ad.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`note`	No
`backend`	No
`available`	Yes
`library_id`	No
`transcript`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.6.1Oct 6, 2026
- removedInput schema / $schema
```
Removed value: -"http://json-schema.org/draft-07/schema#"
```
- removedInput schema / additionalProperties
```
Removed value: -false
```
- removedOutput schema / $schema
```
Removed value: -"http://json-schema.org/draft-07/schema#"
```
First observedv0.4.0Sep 1, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so safety is covered. The description adds genuinely new behavioral context: the backend dependency and the graceful-degradation behavior ('explains that rather than failing silently'), which an agent needs to interpret a non-transcript response. It does not contradict any annotation.

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?

Three short sentences, zero filler, and the core purpose is front-loaded before the backend caveat. Every sentence carries distinct 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?

An output schema exists, so return values need no explanation, and annotations cover the safety profile. The description supplies the key operational caveat (backend requirement, non-silent failure), though it omits any note about non-video ads or transcript availability limits.

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?

There is a single required parameter whose schema description (100% coverage) already documents it as the Ad Library ID of a video ad. The description adds no extra meaning about the parameter, so the baseline 3 for high schema coverage applies.

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?

States a specific transformation (speech to text) on a specific resource (a video ad) and clarifies the output is the readable spoken script. This is clearly distinguishable from siblings like get_ad or view_ad_creative, which retrieve ad data rather than transcribe it.

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?

The description states a precondition for success ('Only the scrapecreators backend can do this') but never says when an agent should choose this tool over alternatives such as view_ad_creative, nor which ads are eligible. Usage is implied (you want the transcript of a video ad) rather than explicitly guided.

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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