Alternatives
Products that do what PhysicsThinking does
AI agents discover physics through MCP.
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Connect Your AI to Institutional-Grade Market Intelligence Plug any AI client, from ChatGPT to custom agents, directly into our financial data engine. Get real-time stock prices, fundamentals, institutional trading insights, and other financial data delivered through a universal Model Context Protocol (MCP) server.
Mar 2026 · financialdata.net
- 18LA
Hi HN, I'm excited to share Latitude Agents—the first autonomous agent platform built for the Model Context Protocol (MCP). With Latitude Agents, you can design, evaluate, and deploy self-improving AI agents that integrate directly with your tools and data. We've been working on agents for a while, and continue to be impressed by the things they can do. When we learned about the Model Context Protocol, we knew it was the missing piece to enable truly autonomous agents. MCP servers were first thought out as an extension for local AI tools (i.e Claude Desktop) so they aren't easily hostable in…
2025 · latitude.so
- 19JA
Hey HN, I'm one of the creators of joinly.ai, an open-source solution that makes browser-based video conferences accessible to AI agents, allowing you to interact with them in real time. Think of it as a connector layer that brings the functionality of your AI agents to your meetings, allowing you to essentially build your own custom meeting assistant. We didn't want to build yet another Python framework for creating agents with its own syntactic sugar that you have to learn. That's why we opted for a different approach, utilizing an MCP server. Our MCP server provides essential meeting…
2025 · github.com
- 20WB
Humans compete to improve their AI agents on benchmarks. But what if agents could collaborate and compete on their own? We built Hive, a crowdsourced platform where agents can evolve solutions together. One agent begins to tackle a task, iteratively improving its code. Then other agents join. They read each other’s runs, fork the best ideas, propose new ones, and push the solution forward together. We already have agents working on benchmarks like Tau2-Bench, Terminal-Bench, and ARC-AGI-2, with more tasks coming soon. We also support the new OpenAI Parameter Golf Challenge, and you can…
Mar 2026 · hive.rllm-project.com
- 21TM
AgentRQ is a (optionally) human-in-the-loop, self learning closed loop task manager for agents. Agents can create and schedule tasks for themself and work on them on their own schedule. In high level it comes with one supervisor MCP that controls workspaces(worker agents) and unlimited number of isolated workspace MCPs (self learning agents). Each workspace/agent has a mission/persona for the agent. And self-learning-loop note. I am using it about 6 weeks in production, and completed more than 500 tasks. I just released the opensource version(as is in production) under Apache 2.0…
Apr 2026 · github.com
- 22IB
Hi HN, I'm the creator of this project. For the past months, I've been working on building an AI agent that could move beyond simple generation and tackle inventive challenges autonomously. The core idea was to create a system with a "metacognitive loop"—the ability to recognize when it's stuck on a fundamental problem and then launch a sub-mission to solve that specific bottleneck before continuing. The linked article is a deeper introduction to the system's architecture and a snapshot from a recent run. I tried to design it to be evidence-grounded and self-critical to avoid the pitfalls of…
2025 · robw1se.substack.com
- 23AP
Hi HN. I built a prototype AI physics tutor that can interpret, draw, and edit free body diagrams. Lately I've been transfixed with generating diagrams with LLMs. If you pipe generated JSON through a D3.js renderer, you can get pretty consistent SVG results with the smarter models. This physics tutor prototype is an example of an application. For a couple premade scenes, you can ask it to make an FBD, decompose an angled force into components, run through the math of Newton's Second Law, or off-road and try and generate a FBD for a scene of your own description. I previously made a similar…
2025 · physicsviewer.com
- 24IM
Recently, I was exploring the OpenAI Agents SDK and building MCP agents and agentic Workflows. To implement my learnings, I thought, why not solve a real, common problem? So I built this multi-agent job search workflow that takes a LinkedIn profile as input and finds personalized job opportunities based on your experience, skills, and interests. I used: - OpenAI Agents SDK to orchestrate the multi-agent workflow - Bright Data MCP server for scraping LinkedIn profiles & YC jobs. - Nebius AI models for fast + cheap inference - Streamlit for UI (The project isn't that complex - I kept it…
2025
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