The Model Context Protocol crossed 10,000 published servers under the Linux Foundation's Agentic AI Foundation. As someone who's integrated dozens of AI systems, here's why this number matters more than any benchmark.
March 2026 marks a turning point — AI coding tools evolved from assistants to autonomous agents. As a Technical Lead, here's what you actually need to know to navigate JetBrains Central, GitHub Agent HQ, Dapr Agents, MCP, and the multi-agent revolution.
A practical, hands-on guide to automating Developer, QC, and Tech Lead workflows across three maturity levels — Manual, Agentic (Claude Code), and Fully Autonomous (NanoClaw). With mermaid diagrams, real configs, BDD examples, and step-by-step instructions you can implement today.
Most people are stuck in Phase 1 of AI — asking questions and doing work themselves. Phase 2 is Agents: you set a goal, the agent delivers results. Here's the complete breakdown of what changed, how it works, and why it matters.
How to build a coordinated Claude agent team: defining agent skills, assigning responsibilities, orchestrating multi-agent workflows, and collaborating across agents to deliver a real software product from idea to production.
What MCP is, how to configure servers in .mcp.json, the top servers by category (GitHub, Playwright, databases, search, design, cloud), performance pitfalls, and why you should limit yourself to 2-3 per project.
A complete guide to connecting Jira, Linear, GitHub, and Playwright MCP servers with Claude Code to auto-generate BDD tests from ticket acceptance criteria, execute them against a live app, and report results back.
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