GMGN User Filters 3,200+ Tokens with Claude Code Integration
GMGN User Filters 3,200+ Tokens with Claude Code Integration
🔍 Real alpha filtering
A GMGN user developed a custom filtering system using Claude Code and the GMGN OpenAPI to scan over 3,200 tokens in four days, identifying legitimate projects among trending tokens.
Key Features:
- Filters out bundled, botted, or exit liquidity tokens
- Uses GMGN's real-time data for faster signal detection
- Open-source implementation available on GitHub
How to Build Your Own:
- Create an API key at gmgn.ai/ai
- Access the open-source repository at github.com/GMGNAI/gmgn-skills
- Supports 60+ data metrics for granular filtering
- Enables 0.3s on-chain execution speed
The system addresses a common problem: most trending tokens are manipulated by the time they appear on standard feeds. Custom filtering helps traders identify genuine opportunities before they become widely known.
This is informational content only, not investment advice. Always conduct your own research.
💰 This is how real alpha gets found GMGN user built a filtering system with Claude Code + the @gmgnai OpenAPI: 3,200+ tokens scanned in 4 days, only the real runners survived. 🔥 Most "trending" tokens? Bundled, botted, or already exit liquidity by the time you see them. Speed
how i use claude code & the @gmgnai api to catch every runner of the day and filter out the noise. most trending tokens aren't tradeable. bundled, botted, or exit liquidity by the time you see them. filtering matters more than speed. 4 days running. 3,200 tokens entered the
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