Alternatives
Products that do what RunKit – a browser based tmux manager does
RunKit is a browser based tmux manager that works great on a phone over Tailscale. I created it to be able to run several AI agents in parallel, after trying out several existing tools. There's no database (state is read live from tmux). Right now, its the first thing I install on any server, and from there on RunKit becomes the management cock-pit for that server. Also, for running several agents in parallel, RunKit has been a lifesaver. It shows the status of all running agent on the left panel, and sends you a notification anytime an agent is stuck. Please try it out, and let me know if…
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2016 · github.com
- 11NL
Built this because I was tired of every AI tool shipping my data to someone else server n0x runs the full stack LLM inference via WebGPU, autonomous ReAct agents, RAG over your own docs, sandboxed Python execution via Pyodide all inside a single browser tab. No account No keys No backend Models download once, cache in IndexedDB permanently. Biggest challenge was context window budgeting for the agent loop and making the WASM vector search non-blocking. Happy to talk architecture. GitHub: https://github.com/ixchio/n0x | Live demo: https://n0x-three.vercel.app
Mar 2026 · n0xth.vercel.app
- 12RM
RunAgent eliminates the complexity of AI agent deployment across different frameworks and languages. Today's developers face deployment nightmares with fragmented frameworks (LlamaIndex, LangChain, LangGraph, CrewAI, Letta, Agno, etc.) each requiring different deployment processes, creating unnecessary friction. The Solution: Like MCP (Model Context Protocol), RunAgent provides a standardized approach to agent deployment. Developers simply provide a config file and their agent code - RunAgent handles the rest with REST API and WebSocket (Streaming and non streaming). Our open-source platform…
2025 · github.com
- 13RA
Hey HN, There’s been a lot of interest recently in meta-harnesses, loops, and multi-agent orchestration. Obviously, there are already a lot of good tools: Conductor, cmux, the native Codex / Claude Code apps, etc. For my own use cases, I’ve felt that the orchestration layer tends to feel overengineered. I mostly wanted a simple local harness (i.e Pi) for running and tracking CLI agents with the ability to hop in (via tmux). Relaymux is my opinionated attempt at that. A few design principles: - The frontend is just Telegram / iMessage / CLI. If I want more visibility, I hop…
Jun 2026 · github.com
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2022 · github.com
- 15DY
Hey HN! I'm open-sourcing DataKit today. GitHub: https://github.com/datakitpage/datakit Live demo: https://datakit.page DataKit is a browser-based data analysis platform that processes multi-gigabyte files (CSV, Parquet, JSON, Excel) entirely client-side using DuckDB-WASM. Your data never leaves your browser. What it does: • Process large files (tested up to 20GB) without any server • Full SQL interface powered by DuckDB compiled to WebAssembly • Python notebooks via Pyodide for data science workflows • Connect to remote sources (PostgreSQL, MotherDuck, S3) with…
Dec 2025 · github.com
- 16AM
Hi HN, Excited to share Agno, a framework and runtime for multi-agent systems. Think of it as FastAPI for AI Agents. At its core is the AgentOS, a high-performance server/runtime that helps you run and manage AI agents, multi-agent teams, and step-based agentic workflows — all inside your own cloud, with full privacy and no external data sharing. What makes it different • Fast & lightweight — Agents instantiate in ~3μs and use ~6.6 KiB of memory on average (tested on M4 MacBook Pro). • Runtime architecture — Async, stateless, horizontally scalable runtime built on FastAPI. • Integrated…
Oct 2025 · agno.link
- 17AR
If you're interested in exploring what LLM-based agent systems these days actually do to solve certain benchmarks such as SWEBench or WebArena, we created a small leaderboard with our team, that allows to view a lot of public and OSS agent results including all the runtime traces (the step-by-step reasoning behind the scenes). Looking at traces is actually quite interesting, as they reveal a lot about the inner working and shortcomings of current agent system, e.g. see https://explorer.invariantlabs.ai/u/invariant/webarena--SteP... for an example trace.
2024 · explorer.invariantlabs.ai
- 18LT
Running multiple coding agents could make user losing track of what they were doing. Once subagents start spawning other subagents, basic questions get hard to answer: what is running right now, what tool did it just call, did the child agent actually do what the parent asked. Lazyagent is a terminal TUI that collects events from Claude Code, Codex, and OpenCode and shows them in one place. It groups sessions from different runtimes by working directory, so Claude and Codex runs on the same repo appear under the same project. From there you can: - Filter events by type: tool calls, user…
Apr 2026 · github.com
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- 20IB
Link: https://docs.trysoma.ai/ For the past ~9 months I’ve been building Soma, an open-source AI agent & workflow runtime written in Rust, with a TypeScript SDK (Python coming soon). It’s not a framework; it’s meant to sit underneath whatever agent/tooling code you already write (Vercel AI SDK, LangChain, custom code, etc.). It provides features around your framework + a better DX for building agents. I’ve tried to take a Next.JS model: open-source, good DX, self-deployable. I originally set out to build a vertical back-office/operations product for SMEs. I needed a…
Dec 2025 · docs.trysoma.ai
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- 22DA
I built an open-source desktop app for running and monitoring Python agents that talk over TCP. It works on macOS, Linux, and Windows. The basic idea is simple: if a repo has an `agent.py` entrypoint, the app can import it from GitHub, install `requirements.txt` if needed, connect it to a TCP server, and show what it is doing in one UI. Current features: * import agent repos from GitHub, including private repos * run agents through `agent.py` * optional `requirements.txt` support * optional `id.json` for agent metadata * connect agents to TCP servers * inspect message flow in one place *…
Mar 2026 · github.com
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There's been some interesting work lately with BrowserAI (runs LLMs in the browser using WebGPU) enabling local, private AI processing. Now, the team has released BrowserAgent - a no-code tool built on top of it. BrowserAgent lets you create custom AI workflows using a drag-and-drop interface, all within your browser. This means personalized web summarizers, research assistants, or content generators can all run locally with no cloud costs and full data privacy. Check it out here - https://browseragent.dev Key features include: - No-Code Workflow Builder: Design custom AI agents…
2025 · browseragent.dev
- 24SA
Problem Statement: A few months ago, I was outside of my city. I was on a bus when one of my team members messaged me saying users were unable to read the product description PDF. I had to wait 3 more hours until I got back home, opened the laptop, and SSH'd into the server to find out what was wrong. In that moment I realized that being able to manage a server from a phone is very important when a laptop is not nearby. What it does: It is a UI wrapper over standard SSH command outputs. It parses the SSH output and shows the results in UI elements, and also translates your actions to…
Jun 2026 · play.google.com
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