{"version":"1.0","type":"rich","title":"Gist 332eae147ca220d8fe012a2cd5742f65","description":"This example shows a TypeScript-based trading alpha detection agent that monitors social media and market data to identify cryptocurrency trading opportunities. The agent uses the Mastra framework to combine multiple MCP servers, including Recall for decentralized storage and omnifeeds for Twitter and Substack data collection. It tracks token prices, mentions, and volume changes from CoinGecko, computes heat values based on social signals and price movements, and stores structured data including chain-of-thought logs, trading predictions, and token price histories in Recall buckets. The system maintains an agent strategy document that evolves over time, documenting trading rules and decision parameters, with all data persisted through the Recall client using viem wallet authentication.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-332eae147ca220d8fe012a2cd5742f65?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}