Opera's Fully Agentic AI Browser

Today’s top AI Highlights:

1. Agentic browser that can take actions and build projects while you sleep

2. This opensource framework is the easiest way to build MCP servers

3. Mistral’s new embedding model built specifically for code

4. AI video you can watch and interact with in real-time

5. Opensource framework to unit test LLM outputs like Pytest

& so much more!

Read time: 3 mins

AI Tutorial

Picture this: you're deep in a coding session when you need to update your project documentation in Notion. Instead of context-switching to a browser, navigating through pages, and manually editing content, you simply type "Add deployment notes to the API docs" in your terminal. The magic happens instantly—your Notion page updates without you ever leaving your development environment.

In this tutorial, we'll build a Terminal-based Notion Agent using MCP and Agno framework. This agent will allow you to interact with your Notion pages through natural language commands directly from your terminal, enabling operations like content updates, searches, block creation, and comment addition.

We share hands-on tutorials like this every week, designed to help you stay ahead in the world of AI. If you're serious about leveling up your AI skills and staying ahead of the curve, subscribe now and be the first to access our latest tutorials.

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Latest Developments

Build Full MCP Servers with Zero Boilerplate 🤖🔗⚡️

Model Context Protocol has become the de facto standard for connecting AI agents to external tools and services. MCP servers are no longer nice-to-have integrations, they're table stakes for any service that wants to be accessible to the growing ecosystem of AI agents. But building production-ready MCP servers is still a nightmare. The official spec gives you the protocol basics, but leaves you to figure out authentication, observability, error handling, and deployment on your own. You’d be spending weeks just getting the plumbing right!

Golf is an opensource framework that makes it radically simple to build production-grade MCP servers. You just write the tools, prompts, and resources you want agents to call. It handles everything else - routing, auth, telemetry, error reporting, and deployment. No decorators, no schema definitions, no transport configuration - just your business logic. Get your server up and running with authentication, monitoring, and tracing in under 60 seconds.

Key Highlights:

1. Zero Boilerplate - It’s a simple file-based approach where each Python file automatically becomes a live agent endpoint. Write your tool logic in plain Python functions, and Golf handles routing, schema compliance, and API generation automatically.

2. Production Infrastructure - Unlike frameworks that give you the protocol SDK and wish you luck, Golf provides complete production infrastructure from day one. Authentication flows (OAuth and API keys), OpenTelemetry tracing, structured logging, rate limiting, and error monitoring work out of the box.

3. Deploy in 60 Seconds, Not 60 Hours - Get a live, observable server with real-time traces and monitoring in under a minute. The same codebase works everywhere - from local development to production - with zero vendor lock-in, whether you self-host or use Golf's managed platform.

Stop fighting infrastructure and start shipping agent tools. Try Golf and have your first production MCP server running in the next 5 minutes.

Agentic Browser That Can Browse and Take Action For You 🌐💪

Autonomous web AI agents are getting their biggest upgrade yet - they're moving directly into your browser. What started as standalone tools that could navigate websites and fill forms has evolved into something much more ambitious: browsers that can actually think, plan, and execute complex tasks without you babysitting every click.

Opera just dropped Opera Neon, a fully agentic browser that shows what browsing should look like when AI agents can handle the heavy lifting of actually getting stuff done online. Built on Opera's Browser Operator, this browser can chat contextually about whatever page you're on, execute multi-step web tasks like booking trips or filling forms, and even build complete projects from scratch - games, websites, reports - while you're offline. The "Make" feature is particularly wild: you can literally ask it to create something, walk away, and come back to find it completed and hosted, ready to share.

Key Highlights:

1. Agents in Three-Modes - Opera Neon offers Chat (contextual AI that understands your current webpage), Do (autonomously performs tasks like bookings and shopping), and Make (creates full projects like games and websites). This trio covers everything from quick AI chats to vibe-building.

2. Local-First - The browser handles most AI processing locally on your machine for privacy, but scales to cloud servers when building complex projects. Your browsing data stays private while still giving you access to powerful capabilities, solving the typical trade-off between privacy and computational power.

3. True Multitasking - Unlike other web AI agents that handle one task at a time, Neon can manage multiple simultaneous projects in the background. You can request several different creations, continue browsing normally, and return to find completed projects ready for use.

4. Built-in Hosting - Neon doesn't just create digital projects; it automatically hosts them and provides sharing capabilities. Whether it's a game, report, or web application, everything gets deployed without needing servers or deployment pipelines. You can basically move from "AI made this" to "people can actually use this."

Quick Bites

Mistral AI has released Codestral Embed, a new embedding model built specifically for code. It performs especially well for retrieval use cases on real-world code data, great for high-performance retrieval in coding agents and dev tools. It outperforms Voyage Code 3, Cohere Embed v4.0, and OpenAI’s embedding model across multiple benchmarks like SWE-bench, code2code, and text2sql. Even its smallest config (256-dim, int8) delivers better results than full-sized rivals. Available via API for $0.15 per million tokens.

You've likely explored the latest in AI video generation, but now Odyssey.world is inviting you to step beyond just watching, allowing you to actively interact with AI-imagined scenes as they unfold in real-time. They've built a new world model that dynamically generates and streams these interactive video frames every 40ms. The visuals are still glitchy, but it already feels like stepping into a strange dream, and it's live for anyone to try (if GPUs are free).

Retool has launched Retool Agents, a public beta of autonomous AI workers that can run your internal business workflows end-to-end - from issuing refunds to updating inventory - by directly using your company’s APIs, SQL, and tools. These agents don’t just give suggestions; they observe, reason, and act using the logic and workflows you’ve already built inside Retool.

You pay for these agents by the hour, not tokens or seats, with pricing starting at $3/hour. Over 100 million hours of work have already been automated using Retool Agents, with companies like AWS and Databricks among early adopters.

DeepSeek has released an updated version of its R1 model on Hugging Face, under the MIT license. R1 has always been excellent at coding, and this new version has climbed to the top of LiveCodeBench among opensource models, outperforming Qwen3-235B and even Claude 3.7 Sonnet (Thinking). The Hugging Face repo includes only config files and weights, with no extra documentation yet.

Tools of the Trade

1. Simplex: Build production-grade AI web agents in a few lines of code to automate workflows on legacy portals and websites that lack proper APIs. It provides constrained web agents, anti-bot protections, workflow caching, and debugging tools to build reliable automations with legacy systems at scale.

2. MindFort: A team of specialized AI agents to run fully autonomous penetration tests on your web apps, identifying real vulnerabilities like SQL injection, misconfigurations, and session hijacking. It scores each risk, suggests fixes, and can run continuously in auto-mode without any manual setup or installation.

3. DeepEval: Opensource framework that lets you unit test LLM outputs, like RAG pipelines, agents, and chatbots, using evaluation metrics such as hallucination, answer relevancy, and RAGAS. It runs locally, works with any model, supports CI/CD, and gives you full control to write and run LLM test cases in just a few lines of code.

4. Awesome LLM Apps: Build awesome LLM apps with RAG, AI agents, MCP, and more to interact with data sources like GitHub, Gmail, PDFs, and YouTube videos, and automate complex work.

Hot Takes

1. DeepSeek-V4/R2 will crush american labs if they don't get crazy and go for 90% margins like Anthropic ~
   Lisan al Gaib

   
   

2. The pressure on OpenAI for GPT-5 is insane. If it flops, the AI hype train dies right there. A lot of people (me included) will call it: the bubble popped. If GPT-5 isn’t a clear, major leap, not just the model, but the whole ChatGPT experience, then it’s fucking over. But I don’t think that’ll happen. I don’t expect GPT-5 will just be a smarter model. I expect it’ll reinvent the entire product, cleaner, cooler, just straight-up better across the board. Not just a model upgrade. A full product upgrade. It cannot afford to be mid in any way.

   So yeah. No pressure. ~
   Flowers

That’s all for today! See you tomorrow with more such AI-filled content.

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