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Connect AI Agents 8,000+ Apps
PLUS: TypeScript agents with minimal coding, Fully opensourced YOLO competitor
Shubham Saboo & Gargi Gupta
March 25, 2025
In partnership with
Today’s top AI Highlights:
No chains No pain: Build AI agents with TypeScript decorators
Connect AI agents to 8000+ tools via MCP without a single line of code
Roboflow’s fully opensourced YOLO competitor
China's DeepSeek quietly pushes upgraded DeepSeek V3
AI orchestration layer to cut API costs by 40-95%
& so much more!
Read time: 3 mins
AI Tutorials
In this tutorial, we'll show you how to create your own powerful Deep Research Agent that performs in minutes what might take human researchers hours or even days—all without the hefty subscription fees. Using OpenAI's Agents SDK and Firecrawl, you'll build a multi-agent system that searches the web, extracts content, and synthesizes comprehensive reports through a clean Streamlit interface.
OpenAI's Agents SDK is a lightweight framework for building AI applications with specialized agents that work together. It provides primitives like agents, handoffs, and guardrails that make it easy to coordinate tasks between multiple AI assistants.
Firecrawl’s new deep-research endpoint enables our agent to autonomously explore the web, gather relevant information, and synthesize findings into comprehensive insights.
We share hands-on tutorials like this 2-3 times a 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.
Latest Developments
Magma is a low opinion Typescript framework to build AI agents without the complexity — skipping chains, abstractions, and infrastructure headaches. Think of it as Vercel, but for AI agents.
No complex chains, no confusing abstractions - just write the logic you want your agent to have. The deployment, scaling, and real-time communication are handled by Magma’s infrastructure. Plus, with its TypeScript-first approach, you get type safety, easy integration, and the ability to scale agents seamlessly, making it possible to go from prototype to production in no time.
Key Highlights:
Zero Abstraction Hassle - Build your agent as a simple TypeScript class without wrestling with complex chains or confusing abstractions. Just add methods to your class and decorate them with @tool to enable functionality like database searches or API calls.
Model AGnostic - Switch between OpenAI, Anthropic, Google, and Groq models by changing a single config parameter. Your agent's code stays the same regardless of which provider you're using.
Built for Production - Deploy your agent in seconds with built-in infrastructure that handles scaling, real-time communication, and multi-tenancy. Each user gets their own agent instance, and you don't have to worry about the DevOps headaches.
Developer-Friendly Middleware - Add custom logic with middleware that runs before/after completions and tool executions. Perfect for implementing validation, logging, or data sanitization with minimal boilerplate code.
Stop taking manual meeting notes
Put your meetings on autopilot and wow your team and customers.
Fellow is the AI meeting assistant that:
✔️ Auto-joins your Zoom, Google Meet, and Teams calls to take notes for you.
✔️ Tracks action items and decisions so nothing falls through the cracks.
✔️ Answers questions about meetings and searches through your transcripts, like ChatGPT
Try Fellow today and get unlimited AI meeting notes for 30 days.
Zapier has launched its own Model Context Protocol (MCP), connecting AI agents directly to 8,000+ apps enabling them to perform over 30,000 actions - without requiring any API integration code. This lets any MCP client like Cursor move beyond conversation to perform real tasks like managing tickets, sending messages, and updating records across platforms like Slack, Google Workspace, and Jira. It even simplifies the integration with LangChain AI agents.
Setup is quick and straightforward - generate an MCP endpoint, configure your desired actions with granular control, and paste it into any MCP-compatible AI assistant.
Key Highlights:
Immediate AI action - Transform your AI agents from just a chat tool into a functional extension that can send messages, create tickets, manage merge requests, and interact with real-world applications through Zapier's extensive app ecosystem.
Code-free implementation - Get started in minutes with a three-step process: generate your endpoint, select and configure which specific actions your AI can perform, and connect it to your AI assistant - no complex coding or API integration required.
Granular permissions control - Restrict exactly which apps, accounts, and actions your AI can access with customizable settings for each integration, ensuring your AI operates within appropriate boundaries.
Platform integration - Use the integration with tools like Cursor or other custom-built MCP client, with free access for individuals (up to 40 tool calls per hour, 80 per day, and 160 per month).
Quick Bites
Roboflow has just released RF-DETR, a fully open-sourced object detection model that sets a new benchmark for real-time visual recognition. Available under an Apache 2.0 license in two sizes, this transformer-based architecture outperforms existing solutions while maintaining excellent speed for time-sensitive applications. For teams working on computer vision projects, RF-DETR offers a compelling alternative to YOLO models.
China’s DeepSeek quietly released a new checkpoint DeepSeek-V3-0324, their latest open-source model boasting 685B parameters, under the MIT license. Early testers say the model is already showing improved performance in coding, math, and complex reasoning tasks, probably even better than DeepSeek R1. DeepSeek-V3-0324 model weights are on Hugging Face. The full model requires substantial storage at 641GB, though a 4-bit version reduces this to 352 GB. Some users say the model is also live on chat.deepseek.com and accessible via Open Router.
MongoDB has released an opensource repository showcasing 100s of code examples for RAG, AI agents, and real-world applications in both JavaScript and Python. The collection integrates with leading AI frameworks like Pydantic AI, LangChain, Haystack, and demonstrates how MongoDB powers real-time AI through unified data storage.
Tools of the Trade
BenchFlow: Open-source framework to integrate and evaluate AI tasks using Docker-based benchmarks with a unified API interface. It features a benchmark hub for sharing and accessing benchmarks, along with an end-to-end reinforcement fine-tuning pipeline.
Portkey's MCP client: Connect AI agents directly to 800+ tools through 90+ MCP servers via prompts. It handles database connections, API requests, secure code execution, and custom tool creation, all managed securely.
Skymel OA: An AI orchestration layer that intelligently distributes processing between device and cloud, cutting API costs by 40-95% and improving performance 2x-10x with a single integration that adapts automatically as AI evolves. It works with all models and providers through one simplified API.
Awesome LLM Apps: Build awesome LLM apps with RAG, AI agents, and more to interact with data sources like GitHub, Gmail, PDFs, and YouTube videos, and automate complex work.
Hot Takes
First agent to connect to all of your work apps — so it can access information and complete tasks across all of them — will probably win. ~
David SacksFirst agent to connect to all of your work apps — so it can access information and complete tasks across all of them — will probably win. ~
signüll
That’s all for today! See you tomorrow with more such AI-filled content.
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