quotaExceeded: the YouTube Data API 403 and its daily quota

The YouTube Data API returns 403 quotaExceeded when a project uses up its daily quota.

403 quotaExceeded: The request cannot be completed because you have exceeded your quota.

Short answer

The YouTube Data API returns 403 quotaExceeded when a project uses up its daily quota. The default allocation, what each call costs, when it resets and how to ask for more.

Diagnosis checked 2026-11-11; sources below.

Why it happens

The Google Cloud project has used its daily YouTube Data API quota: 10,000 units a day for most methods, plus separate buckets of 100 search.list and 100 videos.insert calls. Every request costs at least 1 unit, and the quota resets at midnight Pacific Time. Source: YouTube Data API quota calculator.

Do this now

If the data is yours or your use fits the official terms, switch to the official route: YouTube Data API v3 (Public API). No per-call fee is published; the constraint is the daily quota. Extra quota is not self-serve.
For video metadata, search results and comments at volume, run a hosted route instead of patching your own requests: YouTube Video Metadata & Chapter Extractor. The request below runs it with its published example input through the Apify API (your token, billed at the Store price).
Compare every route, with fields and prices, on the YouTube page.

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run_input = {
    "videoUrls": [
        "jNQXAC9IVRw",
        "dQw4w9WgXcQ",
        "M7lc1UVf-VE"
    ],
    "maxComments": 0,
    "includeChapters": True,
    "includeHeatmap": False,
    "includeEndscreen": False,
    "includeCards": False,
    "includeTranscriptMetadata": True,
    "includeTranscript": False,
    "includeRelatedVideos": 0
}

run = client.actor("vexaloom-labs/youtube-video-metadata-and-chapter-extractor").call(run_input=run_input)
if run is None:
    raise RuntimeError("The Actor run was not found.")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

pip install apify-client

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });
const input = {
    "videoUrls": [
        "jNQXAC9IVRw",
        "dQw4w9WgXcQ",
        "M7lc1UVf-VE"
    ],
    "maxComments": 0,
    "includeChapters": true,
    "includeHeatmap": false,
    "includeEndscreen": false,
    "includeCards": false,
    "includeTranscriptMetadata": true,
    "includeTranscript": false,
    "includeRelatedVideos": 0
};

const run = await client.actor("vexaloom-labs/youtube-video-metadata-and-chapter-extractor").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

npm install apify-client

cURL

curl -X POST "https://api.apify.com/v2/actors/vexaloom-labs~youtube-video-metadata-and-chapter-extractor/run-sync-get-dataset-items"   -H "Authorization: Bearer $APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"videoUrls":["jNQXAC9IVRw","dQw4w9WgXcQ","M7lc1UVf-VE"],"maxComments":0,"includeChapters":true,"includeHeatmap":false,"includeEndscreen":false,"includeCards":false,"includeTranscriptMetadata":true,"includeTranscript":false,"includeRelatedVideos":0}'

Waits for the run and returns the dataset items (runs over 300 seconds return HTTP 408; start an async run instead).

MCP (AI agents)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=vexaloom-labs/youtube-video-metadata-and-chapter-extractor",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Adds this Actor as a tool in an MCP client that takes a remote server URL (Cursor, VS Code, Claude Code) through Apify's hosted MCP server. OAuth sign-in also works without the header. Clients that only start local servers can wrap the URL with npx mcp-remote.

Open YouTube Video Metadata & Chapter Extractor in Apify Store

Routes that work for YouTube data

The official route first, then the catalogue Actors that fit this problem (video metadata, search results and comments), by their published fields. Store figures are the publisher's public numbers.

Routes for YouTube data
Route	Core fields	Price / 1K	Success, 30 days	Link
Public APIYouTube Data API v3	not compared	below		Official docs
YouTube Video Metadata & Chapter Extractor	7/8	$0.99	16 runs, too few to rate	Open in Apify Store
YouTube Search Results & Entity Type Scraper	7/8	$0.99	100% of 21 runs	Open in Apify Store
YouTube Video Comment & Reply Thread Scraper	2/8	$0.99	100% of 24 runs	Open in Apify Store

Official price: No per-call fee is published; the constraint is the daily quota. Extra quota is not self-serve. Compare all 25 YouTube routes.

The facts behind the error

Fact	Value
What it means	HTTP 403 with reason quotaExceeded: the project has used up its quota
Default allocation	100 search.list calls, 100 videos.insert calls and 10,000 units a day for all other methods
Separate buckets	search.list and videos.insert have had their own quota buckets since June 1, 2026
Typical costs	List calls such as videos.list and commentThreads.list cost 1 unit; most writes cost 50 units
Invalid requests	Every request, including invalid ones, costs at least 1 unit
Reset	Daily quotas reset at midnight Pacific Time
Documented recovery	Wait for the reset or file the quota extension request form for YouTube API Services