Instagram Reels Transcript API examples using Apify

Production-ready developer examples for extracting Instagram Reels transcripts with the Apify Actor apple_yang/instagram-transcripts-scraper.

This repository helps developers validate the Actor and integrate transcript extraction into apps, internal tools, databases, batch workflows, and AI/MCP workflows.

It includes cURL, Python, Node.js, Java, Go, and Rust examples.

Apify Actor

• Actor page: Instagram Transcripts Scraper
• Actor ID: apple_yang/instagram-transcripts-scraper

Quick start

1. Create a local environment file:

   cp .env.example .env

2. Add your Apify token:

   APIFY_TOKEN='your_apify_token_here'
   APIFY_ACTOR_ID='apple_yang/instagram-transcripts-scraper'
   INSTAGRAM_SESSIONID=''
   MAX_CONCURRENCY=3

3. Run the cURL quick validation example with a Reel URL as runtime input:

   bash examples/curl/single-url-sync.sh "https://www.instagram.com/reel/your_reel_id/"

4. Choose a language example for production integration:

   • Python
   • Node.js
   • Java
   • Go
   • Rust

Language examples

Language	Single URL	Batch CSV	Directory
cURL	Yes	No	examples/curl/
Python	Yes	Yes	examples/python/
Node.js	Yes	Yes	examples/nodejs/
Java	Yes	Yes	examples/java/
Go	Yes	Yes	examples/go/
Rust	Yes	Yes	examples/rust/

Live demo

If you want to test Instagram transcript extraction without writing code, try the web demo built on top of this API: https://www.transcript365.com

AI and MCP workflows

The API examples in this repository can also be used as building blocks for AI agents and LLM workflows.

For MCP-compatible clients, start with the practical setup hub:

• Use Instagram Reels Transcript API with Apify MCP

Platform-specific guides:

• ChatGPT via Apify MCP
• Claude via Apify MCP
• Gemini CLI via Apify MCP
• Cursor and VS Code via Apify MCP

Analysis and prompt resources:

• AI Agent Use Cases
• Prompt Recipes for Reels Analysis

When to use this repo

• Build transcript extraction into your own app.
• Process batches of Instagram Reel URLs.
• Feed transcript text into internal tools, databases, or content analysis pipelines.
• Avoid maintaining your own video download and transcription infrastructure.

Authentication and input

You must provide your own Apify API token.

Do not hard-code tokens in source code, scripts, docs, commits, logs, screenshots, or shared output files.

Configuration belongs in .env:

• APIFY_TOKEN
• APIFY_ACTOR_ID
• INSTAGRAM_SESSIONID
• MAX_CONCURRENCY

Instagram Reel URLs are runtime input:

• Single URL examples accept a CLI argument.
• Batch examples read URLs from sample-data/instagram-reel-urls.csv.

Actor input

{
  "videoUrl": "https://www.instagram.com/reel/your_reel_id/",
  "sessionid": ""
}

videoUrl is the Reel URL for the current request.

sessionid is optional configuration and should remain blank unless your integration requires it.

Important output fields

• text
• segments
• title
• userName
• likeCount
• commentCount
• videoUrl
• audioUrl
• errMsg
• url

See docs/input-output-fields.md for the full field reference.

Repository layout

.
├── docs/
│   ├── ai-agent-use-cases.md
│   ├── batch-processing-guide.md
│   ├── error-handling-and-retries.md
│   ├── input-output-fields.md
│   ├── production-integration-checklist.md
│   ├── prompt-recipes-for-reels-analysis.md
│   ├── use-with-apify-mcp.md
│   ├── use-with-chatgpt-mcp.md
│   ├── use-with-claude-mcp.md
│   ├── use-with-cursor-vscode-mcp.md
│   └── use-with-gemini-cli-mcp.md
├── examples/
│   ├── curl/
│   ├── go/
│   ├── java/
│   ├── nodejs/
│   ├── python/
│   └── rust/
├── sample-data/
│   └── instagram-reel-urls.csv
├── sample-output/
│   └── .gitkeep
├── .env.example
├── .gitignore
├── LICENSE
└── README.md

License

This project is licensed under the MIT License.