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

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:

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:

Platform-specific guides:

Analysis and prompt resources:

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.