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 workflow super simple. Check it out here: https://lnkd.in/d9sn_7Cw Now I’m curious: Are you implementing MCP in your projects, or sticking with basic function calling? | 52 comments on LinkedIn