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Products that do what I built a tool that turns any API into a CLI for agents does
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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2015 · github.com
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I’ve been working on Code2Docs, an open-source CLI tool that helps developers automatically generate inline documentation (docstrings + comments) for Python code using AI. It’s built to solve a common problem I’ve faced (and seen often in teams): We code by "vibe" — fast iterations, minimal docs, and then forget what the logic was months later. Code2Docs helps bridge that gap by documenting as you go — without breaking your flow. Right now it supports function-level documentation. Planned features include: - README.md generation for projects - API endpoint docs - Database schema…
2025 · code2docs-open-source.netlify.app
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Agents can run non-interactive commands, but they often fail once a workflow needs a real terminal (SSH sessions, installers, debuggers, REPLs, TUIs). I built term-cli so an agent can drive an interactive terminal session (keystrokes in, output out, wait for prompts). And it comes with agent skill for easy integration. It supports in-band file transfer: the agent can move files through the terminal stream itself (same channel as the interactive session), which is useful when the agent doesn’t have scp/sftp, shared volumes, or direct filesystem access across boundaries. Recent example:…
Mar 2026 · github.com
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Hi HN. I'm the founder of Phoenix Labs (ex TikTok, Applied AI) and we're open sourcing our internal tooling today which is like a toolchain / meta-harness for CLI agents useful for really scaling eng and creative work. We are a very small team who's building a very ambitious product so we had to find ways to squeeze every ounce of efficiency that we could get our hands on. Harness strengths of different models (Claude, GPTs) and CLI-harnesses (Claude Code, Codex), safe/robust browser integration to speed up UX/QA testing, teams cli to speed up security reviews and parallelize…
May 2026 · agents-cli.sh
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Fun agent I've been playing with - the idea is it only has access to a bash tool, and it's directed to create CLIs for use (with additional direction to make the CLIs composable, follow the Unix philosophy, etc). It persists these CLIs and knowledge about them get injected into the system prompt dynamically, so each time it runs it gets access to a larger and larger toolset of composable CLIs. One interesting dynamic that's emerged from this is I've started using these CLIs myself since they're the same interface for the agent or for me, and it's turned into kind of non-chat channel to…
Jan 2026 · github.com
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clify is a Claude Code plugin. Give it an API documentation URL and it generates a complete CLI repo: commands for every endpoint, smoke tests, zero npm dependencies. Try it inside Claude Code: 1. /plugin marketplace add derrickko/clify 2. /plugin install clify@derrickko-clify 3. Run /clify You'll have a working CLI in about 10 minutes. I was building agents to manage ad campaigns. Meta's Marketing API has no CLI, and no MCP server either. So I wrote one by hand. It worked, but then I looked at the next API I needed and realized the same problem is everywhere: tons of…
Apr 2026 · github.com
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Hello, my name is Andrei. My friends and I recently built CentralMind Getaway, an open-source tool that automatically generates AI-agent-optimized APIs from your database connection. It’s designed for those who don’t want to expose direct SQL access to their databases and prefer not to spend time building these APIs manually. What it does: - Auto-generates APIs from your database connection, infer schema & sample data using AI - Filters out PII and sensitive data for compliance (GDPR, SOC 2, etc.) - Optimized for AI-Agent with extra meta information and REST and MCP protocol support -…
2025 · github.com
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Hello there HN I experimented with agentic coding recently and I felt the need to track more contextual data by project. Also I felt the need to be able to go beyond the 1D chat to communicate with agents. So I created a local document memory, that is discoverable by agents themselves. The CLI is designed to be easy to pick up by agents. It allows humans to collaborate too by reading / searching / editing documents in the store. I have a Mac native GUI in the review process, I hope it will show up in the App Store soon. You can try it easily, instructions here:…
Jun 2026 · metabrain.eu
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I built a CLI tool that turns codebases and PRs into diagrams so you can quickly understand how things fit together. Originally made it because I couldn't follow my own AI-generated repos. Just shipped a big update: - Switched from D2 to Mermaid for rendering - Tree-sitter AST parsing + agentic flow instead of raw LLM calls. ~50x faster. - Works on any GitHub repo or PR, not just local - Dropped the web frontend, it's just a CLI now - Published as a pip package Still a ton to improve and I'm building fast. Feedback, issues, PRs all welcome.
Feb 2026 · github.com
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Hi HN I recently published docs-cli to pypi. I created this tool because I noticed that my docs kept getting out of sync: I've been using markdown to track the project's implementation and progress, and it became really hard to keep track of everything. This is a simple tool for your agents to ensure that links and indexes are kept fresh. I included the agent-playbook-suite marketplace since this is how I use it. The docs repo was actually built also using it, so dogfooding since day one :) The Agent Playbook Suite includes everything needed to create a project from start to finish. Linked…
May 2026 · artrichards.github.io
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Hey everyone! For the past two weeks my friend and I have been heads-down building Cloi, a fully local debugging agent that runs right in your terminal. You probably know the drill—every AI coding tool asks for API keys, subscriptions, and uploads your entire codebase to the cloud. Cloi does none of that: it runs entirely on your machine, with no cloud, no API keys, no subscriptions, and zero data leaving your system. What Cloi does: - Contextual error capture: Grabs your stack trace, local files, and environment to understand the issue. - Local LLM inference: Spins up Ollama on your box and…
2025 · github.com
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Hi everyone, I built cli-use, a small Python tool that turns any MCP server into a native CLI. The idea is simple: HTTP has curl, Docker has docker, Kubernetes has kubectl — MCP should have a shell-native client too. Why I made it: MCP is useful, but using it through agents has overhead: every session pays schema discovery cost every call carries JSON-RPC framing responses are often verbose JSON when the useful output is just a line or two cli-use converts that into a terse CLI so tools can be called like normal shell commands. Example: pip install cli-use cli-use add fs /tmp cli-use fs…
Apr 2026
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Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…
Mar 2026 · github.com
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Hello HN, I’ve been building AI agents lately and ran into a common "Context Bloat" problem. When an agent has 20+ skills, stuffing every system prompt, reference doc, and tool definition into a single request quickly hits token limits and degrades model performance (the "lost in the middle" problem). To solve this, I built OpenSkills, an open-source SDK that implements a Progressive Disclosure Architecture for agent skills. The Core Concept: Instead of loading everything upfront, OpenSkills splits a skill into three layers: Layer 1 (Metadata): Light-weight tags and triggers (always loaded…
Jan 2026
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Hi HN, I recently open sourced a small tool (Remuda) that I built at work to remove some of the friction of launching and managing agents and figured HN might be interested. I also wrote a post on the company blog that goes into more detail about why I built it and showcases its features: https://www.yendo.com/blog/remuda-an-agent-orchestrator
Jun 2026 · github.com
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