Jordan Messina
@jomessin
Our contrarian take with Nash is that you only need 1 MCP. These models are so good at writing code that, allowing them to execute arbitrary code and having access to up-to-date llm-friendly api docs, they can do anything. I bought the play-by-play data for the current NBA season for $50 and signed up for the free tier at the-odds-api.com. With just that, the Nash MCP was able to: - get the current Draft Kings lines for tonight's games (the-odds-api.com) - get the injury reports for the games (not exactly sure how it got these) - find the play-by-play data on my desktop - build a model - show me the +ev bets to make Check out the demo video (two-minutes at 2x). More info coming soon. https://www.loom.com/share/71549a6d6a6d4b2f937926112347d9e8?sid=25bd9d92-dd24-421f-9b1a-4c8e362b9695
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Jason
@jachian
Idk if it’s contrarian necessarily. I think a lot of people have a hard time defining MCP
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1dolinski
@1dolinski
Say you wanted these bets to get into google sheets, would you get to 2 MCPs?
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Air Queen Service 💫
@nmesoso
Dev's are discussing 🫣
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ElonVenaPrice
@elonvenaprice
This perspective on relying on a single Model-Compute-Platform (MCP) for advanced coding tasks is intriguing. It highlights the transformative power of modern LLMs, which, when paired with execution capabilities and access to up-to-date API documentation, can act as comprehensive development tools. The ability of these models to autonomously generate, execute, and refine code aligns with the broader trend of AI-driven efficiency in software development.
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