Function Calling vs MCP | LLM Tools Face-Off | Live Deep Dive with Rohan & Nisaar: AI Bros Pod Ep 22

🚀 Welcome to another epic AI Deep Dive!
In this livestream, Rohan and Nisaar break down the two most powerful paradigms in AI tool integration:

🔧 LLM Function Calling – direct, structured API calls from within prompts
🔗 MCP (Model Context Protocol) – the future of multi-agent systems and scalable AI tools

Link to Slides :
https://app.napkin.ai/page/CgoiCHByb2Qtb25lEiwKBFBhZ2UaJDcyY2Y2YWZjLThkMGQtNDQ1MC1iZDI2LWE0MWQ2YWQxYjU4YQ

Timestamps
00:00 – Function Calling vs MCP: Overview
01:10 – MCP in scalable AI applications
02:39 – LLM tool calling vs MCP protocols
04:55 – Real-world tool calling in enterprises
06:56 – Real-time APIs: Weather, Stocks
09:39 – Centralizing function logic with MCP
11:03 – What is MCP? Anthropic’s open protocol
13:18 – MCP as a universal interaction layer
15:23 – Server-managed tools in MCP
17:34 – MCP streamlining API updates
19:35 – Parsing outputs in function calling
21:42 – Function calling architecture in LLMs
24:29 – Tool definitions & decision-making
26:35 – Error handling in LLM tool usage
28:44 – Uber booking: Function calling vs MCP
30:42 – MCP server versatility & discovery
32:06 – Seamless Uber-like workflows via MCP
34:08 – Code integration across services
36:20 – Booking PCs via Amazon using MCP
39:07 – Tool registration in MCP clients
41:10 – When not to use MCP
44:32 – Client-server negotiation with MCP
46:34 – Natural language to SQL with function calling
48:46 – Custom tools for database querying
50:40 – Risks in tool dependency
52:57 – AI’s impact on jobs (with humor)
54:59 – Jupyter MCP integration across 5000 apps
57:10 – Text-to-image tools in action
59:21 – Rise of AI app stores
1:00:00 – Long-lived virtual assistants via MCP
1:01:20 – Model size & reasoning for tool calling
1:03:31 – Fine-tuning small models for tool use
1:04:12 – Evolving MCP features for AI platforms
1:05:33 – Structured output reliability
1:06:19 – Simplicity of Function Calling
1:07:40 – Complexity in large tool ecosystems
1:08:21 – Tool selection affects accuracy
1:09:45 – Parameter mistakes & financial impacts
1:10:31 – Custom agent loops for LLMs
1:12:14 – Story generation using function tools
1:13:31 – Specifying tone & writing styles in AI
1:14:53 – MCP & function calling across frameworks
1:15:30 – Toothpaste price jokes & Swiggy
1:16:53 – Deployment challenges in open-source LLMs
1:17:37 – Emojis, Android, and modular ecosystems
1:19:10 – Multimodal models & security focus
1:19:51 – Zomato’s evolving features
1:21:09 – Weather API limitations in MCP
1:21:49 – Model cooperation & toolsets
1:23:06 – Trust & security in MCP servers
1:23:54 – Is MCP overkill for simple tasks?
1:25:25 – Frameworks enhancing tool calling
1:26:02 – SDK support across AI platforms
1:27:16 – jPR’s MCP server & integrations
1:27:53 – VS Code & multi-language MCP SDKs
1:29:18 – MCP Store: The next App Store?
1:29:54 – Web browsing + enterprise AI assistants
1:31:15 – Unified APIs for easy development
1:31:56 – Open-source communities supporting MCP
1:33:17 – Blending digital services with physical world
1:33:59 – Payment servers in India and MCP
1:35:22 – Payment automation via MCP
1:36:02 – Hosting MCP servers efficiently
1:37:35 – Technical complexity of humanoid robots
1:38:18 – Personal robotics & YouTube stories
1:39:53 – AI bots & livestream nostalgia
1:40:46 – Guided PC building collaboration
1:42:24 – Final thoughts & DeepMind’s 100M context
1:43:04 – Overload from large context windows
We’ll cover:

Architecture differences

Real-world use cases

Performance and latency

Developer experience

When to use which (with examples)

Live Q&A with the audience

Whether you're building an AI agent, scaling tools, or just curious about how LLMs really interact with the world—this is for you.

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LLM Function Calling, MCP Protocol, Model Context Protocol, AI Tools, Multi-Agent Systems, Autogen, Langchain, OpenAI GPT Function Calling, Anthropic Claude MCP, AI Agent Frameworks, Build AI Agents, AI Developers, Rohan and Nisaar, Deep Dive AI, Google ADK, Crew AI, Multi Agent Architecture, Function Calling vs MCP, LangGraph, AI Livestream

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