
InstantCLI
Turn any API into a CLI for AI Agents
What it does
Give InstantCLI any API docs and get an intuitive CLI in minutes. Includes binaries + install scripts for all platforms, auto-updates, docs-aware help text, hosting, and more. Built for AI agents.
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Universal CLI by ComposioMar 2026 · composio.dev · ▲161Connect AI agents to 1000+ apps directly from your terminal

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Build high quality Android apps 3x faster using any agent
- IBI built a tool that turns any API into a CLI for agentsMar 2026 · instantcli.com · ▲6
TLDR; I built a tool that turns any API into a CLI designed for ai agents --- Got tired of dealing with bloated context windows from MCP servers and skills that stuff entire API docs into the agent's context CLIs fix this, agents run a single command to self-discover everything an API has to offer So, built a tool to generate them for any api. All CLIs are written in Go, fast and lightweight, no dependencies Help text (via the --help flag) is the killer feature: all context for each command/endpoint/parameter is extracted directly from the user-facing API docs and enhanced with…
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We built OneCLI because AI agents are being given raw API keys. And it's going about as well as you'd expect. We figured the answer isn't "don't give agents access," it's "give them access without giving them secrets." OneCLI is an open-source gateway that sits between your AI agents and the services they call. You store your real credentials once in OneCLI's encrypted vault, and give your agents placeholder keys. When an agent makes an HTTP call through the proxy, OneCLI matches the request by host/path, verifies the agent should have access, swaps the placeholder for the real…

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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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