YouTube MCP Server

Youtube Get Quota Status

youtube_get_quota_status

Report how much of today's YouTube Data API quota is left, and when it resets.

Instructions

Report how much of today's YouTube Data API quota is left, and when it resets.

Returns one entry per bucket — search, stats, shared — with used, remaining and cap for the current quota day, resets_at as an ISO 8601 timestamp, and approximate: true.

Check this before a deliberate search. search is only 100 calls/day and does not recover until resets_at; when it is low it is worth spending a call on a cheaper route instead — youtube_list_channel_videos (2 units from the shared pool) or youtube_search_in_transcript (no Data API quota at all). Treat youtube_search_videos as scarce and deliberate. stats (videos:batchGetStats) and shared are 10,000 units/day each, and quota resets at midnight Pacific Time.

Costs no quota. This reads our own in-process counter, never the API, so it is free to call and cannot itself fail with quotaExceeded — a bucket at 0 is reported, not refused.

The numbers are approximate, and they are ours — not Google's. They count what this server process has spent, so they reset to zero whenever it restarts, and they can under-count calls made before a restart or by another process using the same API key. Google can still refuse a call this tool says is affordable, and a bucket shown as exhausted is exhausted for this process only.

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`buckets`	Yes
`resets_at`	Yes
`approximate`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.4.0Oct 21, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations, the description fully carries the behavioral burden and does so unusually well: it states that the call costs no quota, reads an in-process counter, cannot fail with `quotaExceeded`, reports zero buckets rather than refusing, and that numbers are approximate and process-local. It also warns that Google may still refuse a call the counter says is affordable, covering the main failure-model gap.

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 description is well structured and front-loads the core purpose, then moves through usage, cost, and caveats. It is a bit long for a zero-parameter status tool, and the bucket return-field explanation partly duplicates the output schema, but the caveats are substantive rather than filler.

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

Completeness5/5

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

For a zero-parameter quota-status tool with an output schema and no annotations, it covers what an agent needs: what is returned, when to check it, which alternatives to prefer, that the call is free, and why the numbers may be inaccurate. Nothing material is missing for correct invocation.

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?

There are zero parameters, so the baseline is 4. No parameter description is needed, and the schema is trivially complete.

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?

The description opens with a specific verb and resource: reporting today's remaining YouTube Data API quota and its reset time. This is unambiguous and clearly distinct from every search/retrieval sibling, which it explicitly references as alternatives.

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 says exactly when to use the tool: before a deliberate search, especially when the scarce `search` bucket may be low. It names concrete alternatives with their quota costs (`youtube_list_channel_videos`, `youtube_search_in_transcript`) and frames `youtube_search_videos` as scarce and deliberate.

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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