Automate GitHub trending data collection with FireCrawl, GPT and Supabase
## GitHub Trending to Supabase (Daily, Weekly, Monthly)
## Who is this for?
This workflow is for developers, researchers, founders, and data analysts who want a **historical dataset** of GitHub Trending repositories without manual scraping. It’s ideal for building dashboards, newsletters, or trend analytics on top of a clean Supabase table.
## What problem is this workflow solving?
Checking GitHub Trending by hand (daily/weekly/monthly) is repetitive and error-prone. This workflow **automates collection, parsing, and storage** so you can reliably track changes over time and query them from Supabase.
## What this workflow does
* Scrapes **GitHub Trending** across **Daily**, **Weekly**, and **Monthly** timeframes using **FireCrawl**.
* Extracts per-project fields: `name`, `url`, `description`, `language`, `stars`.
* Adds a `type` dimension (`daily` / `weekly` / `monthly`) to each row.
* Inserts structured results into a **Supabase** table for long-term storage.
## Setup
1. Ensure you have an n8n instance (Cloud or self-hosted).
2. Create credentials:
* **FireCrawl API** credential (no hardcoded keys in nodes).
* **Supabase** credential (URL + Service Role / Insert-capable key).
3. Prepare a Supabase table (example):
```sql
CREATE TABLE public.githubtrending (
id bigint GENERATED ALWAYS AS IDENTITY NOT NULL,
created_at timestamp with time zone NOT NULL DEFAULT now(),
data_date date DEFAULT now(),
url text,
project_id text,
project_desc text,
code_language text,
stars bigint DEFAULT '0'::bigint,
type text,
CONSTRAINT githubtrending_pkey PRIMARY KEY (id)
);
```
4. Import this workflow JSON into n8n.
5. Run once to validate, then schedule (e.g., daily at 08:00).
