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Axe – A 12MB binary that replaces your AI framework

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I built Axe because I got tired of every AI tool trying to be a chatbot.Most frameworks want a long-lived session with a massive context window doing everything at once. That's expensive, slow, and fragile. Good software is small, focused, and composable... AI agents should be too.Axe treats LLM agents like Unix programs. Each agent is a TOML config with a focused job. Such as code reviewer, log analyzer, commit message writer. You can run them from the CLI, pipe data in, get results out. You can use pipes to chain them together. Or trigger from cron, git hooks, CI.What Axe is:- 12MB binary, two dependencies. no framework, no Python, no Docker (unless you want it)- Stdin piping, something like `git diff | axe run reviewer` just works- Sub-agent delegation. Where agents call other agents via tool use, depth-limited- Persistent memory. If you want, agents can remember across runs without you managing state- MCP support. Axe can connect any MCP server to your agents- Built-in tools. Such as web_search and url_fetch out of the box- Multi-provider. Bring what you love to use.. Anthropic, OpenAI, Ollama, or anything in models.dev format- Path-sandboxed file ops. Keeps agents locked to a working directoryWritten in Go. No daemon, no GUI.What would you automate first?

HN · launched Mar 12, 2026 · 227 upvotes (top 3%) · 0 views

Niche: ai agent development platforms · 598 launches, 24 in the last 7 days ▼ -23% · Explore this niche →

Category and tags

  • Horizontal
  • Dev tools
  • Developer
  • AI-native
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Yes A lightweight standalone CLI tool in Go or Rust that compiles down to a small binary to execute structured LLM prompt pipelines is straightforward to build with AI assistance.

Discussion

20 comments analyzed.

Competitors mentioned: crabtalk.ai (daemon + commands architecture), Axe (stateless CLI pipes), nanobot (agent framework)

Concerns raised: nanobot stability issues (v0.1.4.post4, regressions between updates), State persistence and chaining with depth-limited agents, Prompt injection and behavioral drift attack surface, Data consistency across runs with multiple agent interactions, Agent guardrails and preventing unintended behavior

Feature requests: Security primitives and guardrails at the framework layer, Better documentation/blog content for SEO, Public repository access to tiny-agents project

Competitors

Other products that read as similar to this one : 703 launches clear the similarity bar, closest 8 shown.

Attention rank: #50 of 704 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 134 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.