#model-context-protocol
46 episodes
#3755: Hermes vs OpenClaw: Mobile-to-Server AI Frameworks
Why developers are leaving OpenClaw for Hermes—and why mobile-to-server AI interaction remains unsolved.
#3271: LLMs as Parsers, Not Calculators
Stop letting LLMs do math. Use them to parse messy text, then let deterministic code handle the numbers.
#2690: Where Agent Builders Actually Gather
The MCP community, A2A protocol, and Linux Foundation are building the professional identity of agentic AI right now.
#2689: Why CLI Beats MCP for AI Agents Sometimes
Why a plain command-line tool can outperform a purpose-built MCP server for AI agents — and what that means for the protocol's future.
#2683: MCP vs Agent Skills: Context Wars
When 12M token windows arrive, do MCP servers or agent skills win? Plus: federated access for agent teams.
#2551: How Progressive Disclosure Saves MCP from Token Bloat
Why dumping all tool schemas into context breaks accuracy — and three implementations that fix it.
#2541: Agent-to-Agent Scheduling: Building the Calendly for AI
How Google's A2A protocol and Anthropic's Remote MCP could power a new kind of agent handoff for scheduling meetings.
#2478: MCP File Handling: Why Your Base64 Upload Breaks at 4MB
MCP has no standard file input. Base64 breaks at 4MB, presigned URLs need whitelisting, and MinIO workarounds aren't standardized.
#2469: Embedding Model Deprecation: RAG's Silent Killer
When OpenAI retires an embedding model, your RAG pipeline breaks silently. Here’s how to fix it.
#2441: When One Sentence Beats Four Clicks
What happens when you ditch the admin panel and let AI agents manage your systems directly?
#2425: Can One Button Solve Your Streaming Frustrations?
A deep dive into JustWatch, Trakt, Letterboxd, and why your ideal streaming app doesn't exist yet.
#2400: Claude Code’s Hidden Context Tax
How Claude’s eager-loaded primitives silently consume context—and how to optimize your setup for sharper performance.
#2314: One Model or Three? Inside Claude's Architecture
What makes Claude’s Haiku, Sonnet, and Opus different? Discover how architecture shapes their unique strengths and weaknesses.
#2203: Knowledge Without Tools: Why MCPs Aren't Just for Execution
MCPs can be pure knowledge providers with zero tools. Here's why that matters for agents querying government data and authoritative sources.
#2167: Sync vs. Async: Architecting Agents for Scale
Why most enterprise AI agents fail in production has less to do with models and more to do with whether they're built synchronously or asynchronously.
#2075: AI Agents for Israel: Hyper-Local Skills in Action
How reusable AI "skills" are solving real Israeli problems—from shelter navigation to tax compliance.
#2039: CLIs vs. MCPs: How AI Agents Actually Talk to Services
Why give an AI agent a terminal? We compare CLIs and MCPs for AI integration.
#2021: Your Frozen AI Is Getting Smarter (Here's How)
Your AI model might be static, but the system around it can make it learn in real-time.
#2014: Coding Tools Are Secretly System Agents
They call it a coding assistant, but real users are treating it like a personal operating system.
#1945: The "USB-C for AI" Is Finally Here
MCP standardizes how AI tools connect to data, solving the N-times-M integration nightmare.
#1906: Is Your AI Model Agentic-Ready or Just Wearing a Suit?
Native tool calling is the difference between a working product and a debugging nightmare.
#1858: Multi-Model Agents: The Instruction & Context Gap
Mixing AI models creates chaos. Learn the practical fixes for context windows, tokenization, and output formats.
#1857: The Death of the Dashboard
Why build a dashboard when you can just talk to your backend? Meet the MCP server that runs this show.
#1846: Right-Sizing Your Agent's MCP Toolkit
AI agents slow down when overloaded with tool schemas. Just-in-time usage is the fix.