TikTok Ads by Get MCP Ads

tiktok get spark ads

tiktok_get_spark_ads

Read-onlyIdempotent

Retrieves Spark Ads context from specified TikTok ad fields, with a conservative fallback when Spark-specific data is unavailable.

Instructions

Return Spark Ads context from ad fields when available, with a conservative fallback if Spark-specific fields are not supported.

Input Schema

Name	Required	Description
`adIds`	No	Optional ad IDs to inspect.
`limit`	No	Maximum number of returned items or rows. The declared bounds and default apply; use pagination for additional results.
`adgroupId`	No	Optional ad group ID filter.
`advertiserId`	Yes	TikTok advertiser ID

Output Schema

Name	Required	Description	Default
`result`	Yes	Original tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv2.1.1Oct 30, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

changedOutput schema / properties / result / anyOf

Previous value: -[
-  {
-    "additionalProperties": true,
-    "properties": {},
-    "type": "object"
-  },
-  {
-    "items": {},
-    "type": "array"
-  },
-  {
-    "type": "string"
-  },
-  {
-    "type": "number"
-  },
-  {
-    "type": "boolean"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "additionalProperties": {},
+    "properties": {},
+    "type": "object"
+  },
+  {
+    "items": {},
+    "type": "array"
+  },
+  {
+    "type": "string"
+  },
+  {
+    "type": "number"
+  },
+  {
+    "type": "boolean"
+  },
+  {
+    "type": "null"
+  }
+]

First observedv2.0.1Sep 23, 2026

TDQS

C2.8/5.0

Behavior3/5

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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description does add genuine behavioral context — that it degrades to a conservative fallback when Spark-specific fields are unsupported — but never says what that fallback yields or how an agent should detect it happened, which is the key operational detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence with no padding, but the trailing fallback clause is vague relative to its length and the sentence is not front-loaded with what the tool actually returns.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return shapes need not be restated. Still, for a read tool with four filters and a documented fallback mode, the description leaves the agent without enough information to interpret results or choose the right sibling.

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%, so every parameter is already documented in the schema, and the description adds no extra meaning about filtering or scoping behavior. Baseline 3 applies.

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

Purpose3/5

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

It names a verb ('Return') and a resource ('Spark Ads context from ad fields'), but 'Spark Ads context' is loosely defined — an agent cannot tell what fields come back or how this differs from tiktok_get_ads or tiktok_get_spark_organic_joins. The purpose is recognizable but under-specified.

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

Usage Guidelines2/5

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

There is no statement of when to call this instead of tiktok_get_ads, tiktok_get_spark_organic_joins, or the raw endpoints, and no guidance on how adIds vs adgroupId vs advertiserId-only affect the result. Usage is left entirely to inference.

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

Deploy Server