I'm sorry for the misleading title about a sundial, it was a metaphor, and based on the feedback here, if I had to do it again I would pick a different one. :-)
My only worry with these MCP "sensors" is that they add-up to the token cost — and more importantly to the context window cost. It would be great to have the models regularly poll as new data and factor that into their inferences. But I think the models (at least with current attention) will always have a trade-off between how much they are provided and what they can focus on. I am afraid that if I provide Claude numerous senses, that it will lower its attention to our conversation.
But your exciting comment (and again I apologize for disappointing you!) makes me think about creating an MCP server that provides like the position of the sun in the sky for the current location, or maybe some vectorized representation of a specific sundial.
I think the digitized information that we experience is more native to models (i.e., require fewer processing steps to extract insights from), but it's possible that providing them this kind of input would result in unexpected insights. They may notice patterns, i.e., more grumpy when the sun is in this phase, etc.
If it helps, I have several methods of computing the Sun's position at varying degrees of accuracy/complexity, and some sundial code at https://www.celestialprogramming.com/
My only worry with these MCP "sensors" is that they add-up to the token cost — and more importantly to the context window cost. It would be great to have the models regularly poll as new data and factor that into their inferences. But I think the models (at least with current attention) will always have a trade-off between how much they are provided and what they can focus on. I am afraid that if I provide Claude numerous senses, that it will lower its attention to our conversation.
But your exciting comment (and again I apologize for disappointing you!) makes me think about creating an MCP server that provides like the position of the sun in the sky for the current location, or maybe some vectorized representation of a specific sundial.
I think the digitized information that we experience is more native to models (i.e., require fewer processing steps to extract insights from), but it's possible that providing them this kind of input would result in unexpected insights. They may notice patterns, i.e., more grumpy when the sun is in this phase, etc.
Thanks for your thoughtfulness!