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Welcome to VidNavigator API

The VidNavigator Developer API provides transcription, analysis, and structured data extraction across YouTube, TikTok, Instagram, X/Twitter, Facebook, Vimeo, Loom, Dailymotion, and uploaded files. It also supports global YouTube and TikTok discovery plus semantic search over indexed YouTube channel content and uploaded files.

OpenAPI Specification

View the complete OpenAPI 3.0 specification

Get Started

Quick start guide for making your first API call

Authentication

All API endpoints require authentication using an API key passed in the X-API-Key header:
Get your API key from the VidNavigator Developer Dashboard.

Base URL

The API is available at:

Long Videos and Async Jobs

The speech-to-text endpoints run for as long as the media is long, so each one has an async twin. Synchronous calls are limited to 10 minutes of media and reject longer media with 400 video_too_long; the async endpoints have no duration cap and work for short videos too. The async endpoint returns 202 with a task_id immediately. Poll the check_status_url (free), or get called back through a webhook — set a default endpoint in Studio → API or pass webhook_url per request.

Async Jobs

Submit, poll and migrate from synchronous calls

Webhooks

Payload, signature verification and retries

Error Handling

The API uses standard HTTP status codes and returns structured error responses:
Actionable errors also carry a docs_url pointing to the page that explains how to fix them. See Errors for every error code.

Common Error Codes

API Categories

Transcripts

Extract transcripts from YouTube, TikTok, Instagram, X/Twitter, Facebook, Vimeo, Loom, and more

File Management

Upload, manage, and organize audio/video files with namespaces

AI Analysis

Analyze video content with AI for insights and summaries

Data Extraction

Extract structured data from transcripts using custom schemas

Video Search

Discover videos with global YouTube and TikTok search

Semantic Search

Search indexed YouTube channel content and uploaded files using vector similarity