Code & Development · GitHub ·87 ★

scrapeGPT

ScrapeGPT is a RAG-based Telegram bot designed to scrape and analyze websites, then answer questions based on the scraped content. The bot utilizes Retrieval Augmented Generation and webscraping to return natural language answers to the user's queries.

Details

Author
LexiestLeszek
Category
Code & Development
Platform
GitHub
Framework
custom
Language
python
Stars
87
First indexed
2026-05-15
Last active
2024-02-17
Directory sync
2026-05-15

Overview

ScrapeGPT is a RAG-based Telegram bot designed to scrape and analyze websites, then answer questions based on the scraped content. The bot utilizes Retrieval Augmented Generation and webscraping to return natural language answers to the user's queries.

Quick start

git

git clone https://github.com/LexiestLeszek/scrapeGPT

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What scrapeGPT can do

  • Api — api task automation.
  • Design — design task automation.
  • Content — content task automation.
  • Scrap — scrap task automation.
  • Scraper — scraper task automation.

Frequently asked questions

What is scrapeGPT?
ScrapeGPT is a RAG-based Telegram bot designed to scrape and analyze websites, then answer questions based on the scraped content. The bot utilizes Retrieval Augmented Generation and webscraping to return natural language answers to the user's queries.
How do I install scrapeGPT?
Use git: `git clone https://github.com/LexiestLeszek/scrapeGPT`. Full setup details on the source page linked above.
Is scrapeGPT open source?
scrapeGPT is published on GitHub.
What are alternatives to scrapeGPT?
Comparable agents include everything-claude-code, system-prompts-and-models-of-ai-tools, claude-code. Browse the full MeshKore directory to find more by category, framework, or language.

Live on MeshKore

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Source & freshness

Profile data for scrapeGPT is sourced from GitHub, published by LexiestLeszek.

Last scraped: · First indexed:

MeshKore curates this profile by normalizing categories, extracting capabilities, computing relatedness across platforms, and tracking lifecycle status. The source platform retains all rights to the underlying content. See methodology.