Production-Ready AI Agents with MCP-Agent

📖 TUTORIALS & CASE STUDIES

Effective LLM Communication for Developers

Estimated read time: 30 min

This guide to prompt engineering explores techniques for maximizing LLM output quality through effective prompting. Focusing on Gemini via Vertex AI and API integration, it covers prompt structure, context handling, and configuration parameters essential for developers building AI-powered applications.

DIY AI Butler with SQLite and Cron Jobs

Estimated read time: 8 min

A developer shares how they built a practical AI butler using just SQLite and cron jobs. This minimalist approach demonstrates that effective AI assistants don't require complex frameworks, offering a simple pattern for storing context and integrating multiple data sources with LLMs.

Transform APIs into AI-Ready Tools with FastAPI MCP

Estimated read time: 15 min

This guide introduces FastAPI MCP, a powerful tool that transforms FastAPI endpoints into Model Context Protocol-compatible tools. Learn how to expose your APIs to LLMs and AI assistants, enabling seamless integration for RAG systems and AI agents with minimal configuration.

Claude Code Best Practices for Developers

Estimated read time: 25 min

Anthropic shares best practices for Claude Code, their command line tool for agentic coding. The guide covers customization, tool integration, effective workflows, and optimization strategies. Learn how to leverage Claude for test-driven development, GitHub automation, and multi-agent approaches that can dramatically improve your productivity as a developer.

Standardizing LLM Tool Integration with MCP

Estimated read time: 15 min

This guide introduces the Model Context Protocol (MCP), a standardized approach for integrating external tools with LLM applications. Using Python examples, it demonstrates how MCP enables consistent tool integration across different frameworks like LangChain and LlamaIndex, supporting both stdio and SSE transport modes.

Microsoft's Free AI Agent Development Course

Estimated read time: 8 min

Microsoft's new course teaches developers how to build AI agents using frameworks like Semantic Kernel and AutoGen. The 10-lesson curriculum covers essential patterns including Tool Use, RAG, Planning, and Multi-Agent systems, with practical code samples supporting both Azure AI Foundry and free GitHub Models.

🧰 TOOLS

Build MCP Servers with FastMCP v2

Estimated read time: 25 min

FastMCP is a Python framework for building Model Context Protocol (MCP) servers that enable secure, standardized interactions between LLMs and custom tools. It simplifies development with decorator-based syntax, supports resource sharing, tool creation, and LLM sampling, making it ideal for developers building RAG systems or AI-powered applications.

GPT-4.1: Coding and Context Improvements

Estimated read time: 20 min

OpenAI's new GPT-4.1 family delivers significant improvements in coding (54.6% on SWE-bench), instruction following, and context handling (up to 1M tokens). These models excel at code diffs, frontend development, and long-document processing while being 26% less expensive than previous versions. The nano variant offers unprecedented speed for low-latency applications.

Terminal-Based AI Coding Assistant from OpenAI

Estimated read time: 15 min

OpenAI's Codex CLI introduces a secure, terminal-based coding assistant that runs commands in a sandboxed environment. This open-source tool enables developers to leverage AI for code generation, refactoring, and testing while maintaining control through configurable approval modes. The CLI integrates with Git and supports custom instructions for personalized coding assistance.

Gemini 2.5 Flash: Control Your LLM's Thinking

Estimated read time: 8 min

Google has unveiled Gemini 2.5 Flash, introducing a groundbreaking "thinking budget" feature that lets developers control the model's reasoning depth. This hybrid model maintains high performance while optimizing costs, allowing developers to fine-tune the balance between reasoning quality, latency, and pricing for different use cases.

Build Custom Classifiers with Mistral AI

Estimated read time: 12 min

Mistral AI's Classifier Factory introduces a developer-friendly approach to creating custom classification models using their ministral-3b model. The platform supports single and multi-target classifications for tasks like intent detection, sentiment analysis, and content moderation, with straightforward API integration and documentation.

Production-Ready AI Agents with MCP-Agent

Estimated read time: 25 min

MCP-Agent introduces a composable framework for building AI agents using Model Context Protocol. It implements patterns from Anthropic's "Building Effective Agents" research and handles MCP server connections, making it easier for developers to create robust agent applications with features like parallel processing, routing, and human-in-the-loop workflows.

📰 NEWS & EDITORIALS

Two Years In: How LLMs Changed Coding

Estimated read time: 15 min

In this analysis, Josh Comeau examines how LLMs are augmenting rather than replacing developers. Drawing from real-world experiences with tools like Cursor and Claude, he demonstrates why human developers remain essential, offering valuable perspective for those concerned about AI's impact on software development careers.

ThoughtWorks Highlights AI Dev Tools Trends

Estimated read time: 15 min

The latest Technology Radar from ThoughtWorks highlights significant trends in AI development tools, with supervised coding agents and RAG innovations leading the way. The report examines the evolution of IDE-integrated AI assistants like Cursor and GitHub Copilot, while also exploring advances in RAG techniques and data management strategies.

Green AI: Sustainable Agent Development

Estimated read time: 12 min

This analysis explores the environmental impact of AI agents, comparing task-specific versus general-purpose models. For developers, it reveals how model selection and architecture choices can significantly affect energy consumption and costs, with task-specific models potentially using 30 times less energy than general-purpose alternatives.

OpenAI's $3B Play for Coding Startup Windsurf

Estimated read time: 4 min

In a significant move for AI coding tools, OpenAI is in talks to acquire Windsurf for approximately $3 billion. The deal would strengthen OpenAI's position in the developer tools market. This is raising concerns to the "model support" in a Open AI owned Windsurf; would they drop all but OAI models, or be biased to those?

Ten Ways LLMs Fail in Production Systems

Estimated read time: 20 min

This analysis examines ten critical LLM failure modes, from hallucinations and biased responses to data retrieval errors. With real-world examples and consequences, it provides essential insights for developers implementing LLMs in production systems, particularly those working with RAG frameworks or building conversational AI applications.