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YouTube MCP by InsightfulPipe

by com.insightfulpipe
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YouTube Data Query

query_data
Read-only

Query YouTube data (Step 3 (FINAL) of workflow).

REQUIRED: Complete these steps first using query_contexts:

  1. request='accounts' - Get workspace_id, brand_id, channel_id AND available_requests

  2. request='actions_details' with platform + report_names or actions - Get detailed body structure

Two platforms: • youtube-analytics: channel_basic, video_performance, demographics, traffic_sources, revenue • youtube-data: channel_info, video_details, playlists, comments

Body must include 'platform' and 'action'. Follow the schema from step 2 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": "query_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds useful behavioral context: this is the final workflow step, it depends on two query_contexts calls, and body must include platform and action. It does not discuss auth, rate limits, or return behavior, but output schema exists and safety annotations cover the main traits.

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?

The description is front-loaded, organized into required steps and platform bullets, and every sentence adds useful information. There is no wasted text, and the workflow ordering is easy for an agent to follow.

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 nested body parameter, output schema, and annotations, the description provides enough context to call the tool correctly: it states prerequisites, platform choices, and required body keys. It is not fully self-contained because detailed body structure is pushed to query_contexts, but that is appropriate for this workflow.

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% and the body parameter is a generic nested object, so the description must compensate. It does provide key semantics by requiring 'platform' and 'action' and listing platform-specific report/action names, but it defers the full body structure to query_contexts and does not document remaining fields.

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?

States a specific verb and resource: 'Query YouTube data', and identifies it as the final step in a workflow with two platform families. The purpose is clear, though it does not explicitly contrast itself with the sibling execute_action.

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

Usage Guidelines4/5

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

Gives explicit prerequisite steps using query_contexts, including request='accounts' and request='actions_details'. It also requires body to include platform and action, but does not state when not to use this tool or compare it directly with execute_action.

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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