Youtube2Text
Offers integration examples for combining YouTube transcription capabilities with Google's AI services
Provides example integrations for processing YouTube video transcripts using Google Gemini AI models
Includes JavaScript implementation examples for integrating YouTube transcription with various AI services
Supports integration with Make (Integromat) for automated video processing pipelines using HTTP modules
Enables workflow automation through n8n using HTTP request nodes or MCP connectors for video transcript processing
Provides integration examples for processing YouTube video transcripts with OpenAI's models for content analysis and generation
Includes Python implementation examples for integrating YouTube transcription with various AI services and processing workflows
Offers TypeScript implementation examples for integrating YouTube transcription capabilities with AI services
Converts YouTube videos into clean, timestampless transcripts by extracting and processing video captions for content analysis and research
Connects with Zapier through MCP integration for triggered workflows involving YouTube video transcription and processing
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Youtube2Texttranscribe https://www.youtube.com/watch?v=dQw4w9WgXcQ"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
YouTube2Text - Video Transcription API
A text extraction service that converts YouTube video content into clean, timestampless transcripts for content analysis, research, and processing workflows. Available as a REST API and as an MCP server for AI agents.
Overview
YouTube2Text transforms YouTube videos into readable text by removing subtitle timing markers and metadata, delivering pure content suitable for:
Content analysis and insights
Text summarization workflows
Research and documentation
Content generation pipelines
AI agent and RAG pipelines
Related MCP server: YouTube Transcript MCP Server
Quick Start
# Get the free shared demo key (no account, 5 videos/month per IP)
curl -s https://youtube2text.org/api/demo-key
# -> {"success":true,"apiKey":"yt_..."}
# Fetch a transcript
curl -s "https://youtube2text.org/api/transcribe?url=https://www.youtube.com/watch?v=VIDEO_ID&maxChars=5000" \
-H "x-api-key: yt_YOUR_KEY"For your own key and higher limits, sign in with Google at youtube2text.org/app/keys.
API Reference
Base URL: https://youtube2text.org
Transcription Endpoint: /api/transcribe (GET or POST)
Complete machine-readable reference: youtube2text.org/api.md (index: /llms.txt). Existing integrations using https://api.youtube2text.org continue to work.
Request Format
Parameter | Type | Required | Description |
| string | Yes | Any YouTube URL form (watch, |
| number | No | Character limit (default and max: 150,000) |
Authentication
Include your API key in the request header:
x-api-key: YOUR_API_KEYAuthorization: Bearer YOUR_API_KEY is also accepted.
HTTP Status Codes
Code | Meaning |
200 | Transcription successful |
400 | Invalid request parameters |
401 | Authentication failed |
404 | Video or transcript not found |
429 | Rate limit exceeded |
500 | Server error |
Error Types
VALIDATION_ERROR: Parameter validation failedUNAUTHORIZED: Invalid API credentialsVIDEO_NOT_FOUND: YouTube video unavailableTRANSCRIPT_UNAVAILABLE: No captions availableINVALID_URL: Malformed video URLRATE_LIMIT_EXCEEDED: Quota or rate limit reached (retryAfterSecondsincluded)YOUTUBE_ERROR: Upstream YouTube failure, retry laterINTERNAL_ERROR: Server-side issue
All error responses include a docsUrl field pointing at the API reference.
MCP Server (AI agents)
The MCP server at https://youtube2text.org/mcp (streamable HTTP) exposes a transcribe_video(url, maxChars?) tool. OAuth 2.1 is supported, so clients like claude.ai connect without manual key handling; an API key header works for everything else.
claude.ai: Settings → Connectors → Add custom connector →
https://youtube2text.org/mcp→ sign in with Google and click Allow.Claude Code:
claude mcp add --transport http youtube2text https://youtube2text.org/mcpClaude API: add
{"type": "url", "url": "https://youtube2text.org/mcp", "name": "youtube2text", "authorization_token": "YOUR_API_KEY"}tomcp_servers.OpenAI Responses API: add
{"type": "mcp", "server_label": "youtube2text", "server_url": "https://youtube2text.org/mcp", "headers": {"x-api-key": "YOUR_KEY"}, "require_approval": "never"}totools.
Integration guides and recipes: youtube2text.org/blog.
Examples
This directory contains examples of how to use the YouTube2Text API with different AI models and in different programming languages.
Python
JavaScript
TypeScript
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