Tutorials

Your AI agent just wrote 200 lines of code. But it has no clue Issue #42 exists. Has no idea the last CI run failed. Can’t see the three open PRs you need reviewed. So you Alt-Tab out, open gh CLI, check manually, paste results back into the agent, and continue the slow dance. So that’s the gap GitHub MCP Server fills — and it’s been sitting at 30,924 stars since GitHub open-sourced it. I’ve been running it for a week across Claude Code, Codex, and Cursor. Let me show you what it actually does. ...

Ever found yourself copy-pasting SQL results from pgAdmin back into your chat with Claude Code, hoping it understands the schema? Yeah, me too. The whole “AI agent can’t see your database” problem has been the single biggest productivity gap in the MCP workflow — until now. Google just dropped MCP Toolbox (formerly genai-toolbox), an open-source MCP server that gives AI agents direct access to 15+ databases. Not a wrapper. Not a middleware. Native database connectivity through the MCP protocol, zero boilerplate. ...

You’ve got a local LLM setup — Ollama, LM Studio, whatever. Now which model do you actually run? That’s the question nobody’s really answering well. HuggingFace shows you download counts. Ollama search tells you what fits in VRAM. But “fits” and “best” are two very different things. I’ve spent way too many afternoons downloading model after model, testing them one by one, only to wonder if there’s something better I missed. ...