VNCNT Labs YouTube Data MCP server

VNCNT Labs Apify examples

Minimal, runnable code for the VNCNT Labs tutorials on pulling SEO and search data through the Apify API. Each folder has the same call four ways: curl, Python (apify-client), Node.js (apify-client) and, where the tutorial uses it, an n8n workflow. The mcp/ folder connects Claude, ChatGPT or Cursor to the same Actors through Apify's MCP server.

Setup

You need an Apify account and an API token (Apify Console > Settings > API & Integrations).

export APIFY_TOKEN=your_apify_token_here   # or copy .env.example to .env and load it; never commit it

pip install -r requirements.txt             # Python 3.10+
npm install                                 # Node 18+

Every example reads the token from the APIFY_TOKEN environment variable. Nothing in this repo contains a real token.

Run

# Python
python 01-keyword-search-volume/python_example.py
# Node
node 01-keyword-search-volume/node_example.mjs
# curl (synchronous: returns the dataset rows as JSON)
./01-keyword-search-volume/curl.sh

Each Python and Node script uses the tutorial's input by default. Pass a JSON file to use your own input:

python 02-competitor-seo-report/python_example.py my-input.json

test-inputs/ holds the smallest useful input for each Actor (1 keyword, 1 domain, 1 term). scripts/smoke_test.sh runs all the Python and Node examples with them.

Note for Python: apify-client 3.x returns a Run object, so the dataset ID is run.defaultdatasetid. Code written for 1.x/2.x uses run["defaultDatasetId"] instead.

n8n

Import 01-keyword-search-volume/n8n-workflow.json (Workflows > Import from file). Then create a Header Auth credential with name Authorization and value Bearer , and select it on the HTTP Request node. Each keyword becomes one n8n item.

Claude, ChatGPT, Cursor (MCP)

Shortened. The full README is on GitHub.