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This MCP server teaches AI Agents how to write production-ready Postgres code. With 4x more constraints, 55% better indexes, and modern patterns. Install in literally one click. 100% Free and Open-source.

More coming in tomorrow's edition of https://t.co/BvTc8nQQW5: Get access to 100+ AI Agent, RAG, LLM, and MCP tutorials with open-source code - All for FREE.

Google just open-sourced A2UI protocol. AI Agents can now generate native UIs on the fly instead of sending walls of text. Flight booking cards, interactive forms, date pickers - all streamed directly to users.

It's available now via API, Mino Platform, and as an MCP server. Available to try for free with 50 Completed Runs. Check it out:

What developers get with Mino: ↳ 85-95% accuracy on complex workflows ↳ Parallel execution across multiple sites ↳ Handles logins, captchas, forms, JavaScript, modals ↳ Returns structured JSON every time ↳ Costs pennies per job

Meet Mino by @Tiny_Fish, a web agents API works differently. It uses AI models to understand sites once, then codifies the logic into deterministic workflows. The agent isn't re-reading pixels and guessing. Gets faster and cheaper with use, not slower and more expensive.

Here's the thing - the next trillion users of the internet are not humans, they are AI agents using websites on our behalf. But: 95% of these websites don't have APIs. Computer use agents are expensive due to vision inference & they hallucinate. Unreliable & unscalable.

Wait, what? This one web agents API → spins up 10 browsers in parallel, → searches for earliest available appointment across all of them, → hands you over the booking links, → and can even book the appointment for you 🤯 100% Free to try.

More such AI tools and projects in https://t.co/BvTc8nQQW5: Get access to 100+ AI Agent, RAG, LLM, and MCP tutorials with open-source code - All for FREE.

Developers waste 20+ hours monthly searching for free tools. This GitHub repo lists 1600+ free services including cloud hosting, databases, CI/CD, APIs, testing tools, and more.

Install it in seconds: Works with Claude Code, Cursor, VS Code, Windsurf, and any MCP-compatible agent. Community-driven with absolutely NO LIMITS. GitHub: https://t.co/mMuJohMYs9 Huge thank you to Tiger Data for collaborating with us on this post.

Here's how: This MCP server allows AI agents to: 1. Search latest PostgreSQL docs semantically, 2. Get curated best-practice skills for common database tasks, 3. Access TimescaleDB knowledge for time-series data workloads. See the difference yourself 👇

The problem is real. AI agents generate Postgres schemas that are outdated, missing constraints and indexes, and ignore modern PostgreSQL features. They're trained on old patterns and random code from the internet. @TigerDatabase’s pg-aiguide MCP server fixes this.

This MCP server teaches AI Agents how to write production-ready Postgres code. With 4x more constraints, 55% better indexes, and modern patterns. Install in literally one click. 100% Free and Open-source.

Open-source context layer for AI agents to self-learn and improve. It goes beyond memory to store conversations, observe tasks, learn from past executions, and collect SOPs into agent's long-term memory. Install and run in literally 2 lines of code. 100% open-source.

More such AI tools and projects in https://t.co/BvTc8nQQW5: Get access to 100+ AI Agent, RAG, LLM, and MCP tutorials with open-source code - All for FREE.

Run 10 coding agents like Claude Code and Codex on your machine. Spin up new tasks while others run, switch between them when they need input. Uses git worktrees to keep each agent isolated. 100% open-source.

More such AI tools and projects in https://t.co/BvTc8nQQW5: Get access to 100+ AI Agent, RAG, LLM, and MCP tutorials with open-source code - All for FREE.

Works with OpenAI, Anthropic, LangChain or any framework. Python and TypeScript SDKs available. Check out the repo and ⭐️ it: https://t.co/0WuTfoISXC

How it works: Your agent completes a task → Acontext extracts the execution pattern → Learns it as a skill block → Stores in a Notion-like workspace → Agent reuses it in future tasks. Only learns from user-confirmed successful tasks. Never touches your system prompt.