A Journey from AI to LLMs and MCP - 9 - Tools in MCP — Giving LLMs the Power to Act
Explains how Tools in the Model Context Protocol (MCP) enable LLMs to execute actions like running commands or calling APIs, moving beyond just reading data.
Explains how Tools in the Model Context Protocol (MCP) enable LLMs to execute actions like running commands or calling APIs, moving beyond just reading data.
Explores methods for testing TypeScript types, including libraries like asserttt and potential built-in language features for type-level testing.
Explains how the Model Context Protocol (MCP) uses 'Resources' to securely serve structured data from systems like files and databases to LLMs.
Explains the benefits of using lowercase names for Git repositories, focusing on cross-platform consistency and avoiding naming collisions.
Explains the architecture of the Model Context Protocol (MCP), detailing its client-server model, core components, and message flow for connecting AI models to tools and data.
A technical guide on creating interactive web maps using Django's GeoDjango module, Pillow for image GPS data, and Leaflet for mapping.
Explores cloud-native Java development, covering microservices, frameworks like Spring Boot, and tools like Docker and Kubernetes for scalability.
Highlights from JavaOne 2025, covering AOT training, garbage collection, Maven builds, and future Java features like value types.
Amazon Q Developer's new inline chat feature in Eclipse IDE helps Java developers refactor, edit, and optimize code directly within the editor.
A critique of fake interactive UI elements like non-clickable 'buttons' that frustrate users, with examples and solutions for better web development.
Explains the Model Context Protocol (MCP), an open standard for connecting AI agents and LLMs to external data sources and tools, enabling interoperability.
Man pages support features like links and text reflow, but current terminal readers like man(1) and less(1) fail to implement them.
Part 3 of a series on SQL Server security, covering auditing, encryption, and secure development practices for DBAs.
Explores AI agent frameworks, their benefits, limitations, and introduces the Model Context Protocol (MCP) for more modular AI systems.
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A hands-on review of Google's updated Gemini Deep Research tool with the 2.5 Pro model, covering its features, usability, and areas for improvement.
Explores how AI tools like GitHub Copilot are transforming software development by automating tasks, improving debugging, and enhancing code quality.
Advanced techniques for using Azure VNet Flow Logs and Traffic Analytics to identify and fine-tune network security rules.
A guide to extending SwiftUI's Text view with custom dynamic styling for individual words or segments using replacements and Markdown.
Explores AI agents, their core components, differences from LLMs, and real-world applications, positioning them as the future of autonomous AI systems.