Fingiendo talento como Inge de Tecnología y Telemetría para Radio & TV. Fan de la tecnología, programación, diseño, foto, música electrónica, F1 y Apple👨🏻💻
Thirty years ago, when it first opened, Toronto’s Rogers Centre was the world's first stadium to have a fully retractable roof. 📹: michaelngynn/Instagram 📍: @SeeTorontoNow, @OntarioTravel#ExploreCanada
algorithms aren’t just for coders; they’re powerful design tools too.
> this book shows how math and algorithms shape patterns, structures, and solutions.
> perfect for engineers, designers, and anyone who wants to merge creativity with computation
@BasicAppleGuy If anyone is interested in how to make the keyboard and a few other accessories, watch my video here, everything is available for free: https://t.co/QZ4VJe0vZX
Confused about the difference between MCP and Function Calling lately?
Are they competing standards at all? (Let’s break it down!)
The short answer: 𝐭𝐡𝐞𝐲'𝐫𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐫𝐲, not competing.
𝗪𝗵𝗮𝘁 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝗖𝗮𝗹𝗹𝗶𝗻𝗴 𝗱𝗼𝗲𝘀:
𝟭. Enables LLMs to identify when to use external tools
𝟮. Structures parameters for tool execution
𝟯. Works within a single application context
𝟰. Leaves the process of running the tool and figuring out how to do so, to you
𝗪𝗵𝗮𝘁 𝗠𝗖𝗣 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗽𝗿𝗼𝘃𝗶𝗱𝗲𝘀:
𝟭. Standardizes how tools are exposed and discovered
𝟮. Creates a consistent protocol for tool hosting
𝟯. Enables ecosystem-wide tool sharing
𝟰. Separates tool implementation from consumption
❗️ 𝗧𝗵𝗲 𝗸𝗲𝘆 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲:
Function calling is about WHAT and WHEN to use a tool.
MCP is about HOW tools are served and discovered in a standardized way.
𝗧𝗵𝗶𝗻𝗸 𝗼𝗳 𝗶𝘁 𝘁𝗵𝗶𝘀 𝘄𝗮𝘆:
➡️ Function calling: "I need to search the web now"
➡️ MCP: "Here's how any tool can be consistently available to any AI system"
𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:
MCP could become the "REST of AI tools" - a ubiquitous standard that prevents ecosystem fragmentation. It allows developers to focus on building great tools rather than reinventing hosting patterns.
𝗛𝗼𝗻𝗲𝘀𝘁 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝘀:
❗️ At the end of the day we are still serving tools for LLMs VIA MCP
❗️ As AI systems grow more complex, we need standardized protocols like MCP for interoperability
❗️ The future is not about choosing between them, but using them together effectively
❗️ Companies that embrace both will build more robust AI systems faster
Ready to try MCP yourself? We just launched our open-source MCP server for Weaviate! Makes adding vector search to any AI system super simple.
Check it out here: https://t.co/BUiuPzptlC
Now I’m curious: Are you implementing MCP in your projects, or sticking with basic function calling?
Happy 257th birthday to Joseph Fourier, whose transform is used in
- quantum mechanics
- signal processing
- spectroscopy
- digital compression of images and data
- solving differential equations
- designing electrical circuits
- ...
One of the best ways to sharpen your brain, and to develop intelligence, is to study mathematics. It challenges and strengthens your mind in a way that very few other things do. It’s like going to the gym -- but for your brain!
- Danica McKellar