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oh-my-pi
⌥ AI Coding agent for the terminal — hash-anchored edits, optimized tool harness, LSP, Python, browser, subagents, and more
I began with pi, and have been using oh-my-pi the last two weeks.
https://github.com/can1357/oh-my-pi
More of a batteries included version of pi.
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Puter.js
Puter.js - The Backend for AI-Generated Apps. One-shot full-stack apps with your existing AI coding tool. Puter.js gives you Auth, Storage, DB, AI & more, with up to 90% fewer AI tokens than other backend platforms.
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pi-mono
Discontinued AI agent toolkit: coding agent CLI, unified LLM API, TUI & web UI libraries, Slack bot, vLLM pods [Moved to: https://github.com/earendil-works/pi]
I use a sandbox example extension with comes with Pi, it uses the anthropic sandbox runtime (bubblewrap on linux). The runtime has one bug and needs one improvement (I've made PRs, no response yet). Pi's sandbox example extension does not block internal tools (read/write) according to rules, I've created a PR but can't submit because of Pi's OSS vacation BS... https://github.com/badlogic/pi-mono/compare/main...k3a:pi-mo... I am quite happy with my patched forks for now
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> while it does seem to do a lot of things very well around extensibility,
https://pi.dev/packages
> I do miss support for permissions,
As soon as your agent can write and execute code, your permissions are just a security theater. If you care, just do proper sandboxing. If not, there are extensions for that.
> MCP
Again, Pi is extensible.
pi install pi-mcp-adapter
Now, you can connect to any mcp.
> and perhaps Todos
At least 10 different todo extensions. Pick which one you like. If you don't like any of them, ask Pi to write one for you.
> and a server mode.
Pi has rpc mode, which is a kind of server. If that's not enough, you could extend it.
> OpenCode seems a lot more complete in that regard,
Yes, but good luck working with Opencode if you don't like their plan-mode. Or todo support. And MCP. You pay their cost in complexity and tokens even if you don't use them or you don't like how they work.
> but I can well imagine that people have adapted Pi for these use cases (OpenClaw seems to have all of these). So it’s definitely not out of the race yet, but I still appreciate OpenCodes relative seeming completeness in comparison.
There's also an oh-my-pi fork if you want an out-of-the-box experience. Still, in my experience, nothing beats Pi in terms of customizability. It's the first piece of software that I can easily make completely to my liking. And I say that as a decade old Emacs user.
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My current fave harness. I've been using it to great effect, since it is self-extensible, and added support for it to https://github.com/rcarmo/vibes because it is so much faster than ACP.
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goose
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
you can run https://block.github.io/goose/ in headless mode (I work on goose)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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I’ve been tinkering with Gondolin, a micro-vm agent sandbox.
Here’s an example config: https://github.com/earendil-works/gondolin/blob/main/host/ex...
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I’m working with a friend to build an ui around Pi to make it more user friendly for people who prefer to work with a gui (ala conductor). You can check out the repo: https://github.com/philipp-spiess/modern
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awesome-personal-ai-assistants
A curated list of open-source personal AI assistants you run on your own devices
there is also pz a drop-in replacement for pi rewritten in Zig. 1.7MB static binary, 3ms startup, 1.4MB RAM idle. Find more at:
https://github.com/elyase/awesome-personal-ai-assistants?tab...
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isagawa-kernel
The self-improving harness for AI coding agents. Drop-in enforcement that the agent builds, follows, and improves — mechanically.
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Nice! I'm curious to hear how you're mapping `read` and `write` to Emacs buffers. Does that mean those commands open those files in Emacs and read and write them there?
Let me also drop a link to the Pi Emacs mode here for anyone who wants to check it out: https://github.com/dnouri/pi-coding-agent -- or use: M-x package-install pi-coding-agent
We've been building some fun integrations in there like having RET on the output of `read`, `write`, `edit` tool calls open the corresponding file and location at point in an Emacs buffer. Parity with Pi's fantastic session and tree browsing is hopefully landing soon, too. Also: Magit :-)
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rho
An AI agent that stays running, remembers across sessions, and checks in on its own. macOS, Linux, Android. Built on Pi. (by mikeyobrien)
Another batteries included pi setup. Built a lightweight mobile webui to run it on termux and code on my phone.
https://github.com/mikeyobrien/rho
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lobu
Open-source control plane and runtime for organisational agents: shared company context, isolated execution, approvals and MCP.
I spent 3 months adopting Codex and Claude Code SDKs only to realize they're just vendor lock-in and brittle. They're intended to be used as CLI so it's not programmable enough as a library. After digging into OpenClaw codebase, I can safely say that the most of its success comes from the underlying harness, pi agent.
pi plugins support adding hooks at every stage, from tool calls to compaction and let you customize the TUI UI as well. I use it for my multi-tenant Openclaw alternative https://github.com/lobu-ai/lobu
If you're building an agent, please don't use proprietary SDKs from model providers. Just stick to ai-sdk or pi agent.
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I've pushed the extension to GitHub at https://github.com/Warbo/pi-extensions/tree/master/extension...
The implementation is pretty terrible: a giant string of vibe-coded Emacs Lisp is sent to emacsclient, which performs the actions and sends back a string of JSON.
It's been interesting to iterate on the approach: watching the LLM (in my case Claude) attempting to use the tools; noticing when it struggles or makes incorrect assumptions; and updating the tool, documentation and defaults to better match those expectations.
I've also written some Emacs Lisp which opens Pi and tells it to "Action the request/issue/problem at point in buffer ''" https://github.com/Warbo/warbo-emacs-d/blob/a13a1e02f5203476...
It feels similar to the file-watching provided by Aider (which uses inotify to spot files containing `# AI!` or `# AI?`), which I've previously used with FIXME and TODO comments in code; but it also works well in non-file things, e.g. error messages and test failures in `shell-mode`, and issues listed in the Emacs UI I wrote for the Artemis bug tracker (Claude just gets the issue number from the current line, and plugs that into a Pi extension I made for Artemis :-) )
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I've pushed the extension to GitHub at https://github.com/Warbo/pi-extensions/tree/master/extension...
The implementation is pretty terrible: a giant string of vibe-coded Emacs Lisp is sent to emacsclient, which performs the actions and sends back a string of JSON.
It's been interesting to iterate on the approach: watching the LLM (in my case Claude) attempting to use the tools; noticing when it struggles or makes incorrect assumptions; and updating the tool, documentation and defaults to better match those expectations.
I've also written some Emacs Lisp which opens Pi and tells it to "Action the request/issue/problem at point in buffer ''" https://github.com/Warbo/warbo-emacs-d/blob/a13a1e02f5203476...
It feels similar to the file-watching provided by Aider (which uses inotify to spot files containing `# AI!` or `# AI?`), which I've previously used with FIXME and TODO comments in code; but it also works well in non-file things, e.g. error messages and test failures in `shell-mode`, and issues listed in the Emacs UI I wrote for the Artemis bug tracker (Claude just gets the issue number from the current line, and plugs that into a Pi extension I made for Artemis :-) )
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guardrails
Supercharge your AI coding agent by defining tasks upfront — working with the model refine requirements before writing a single line of code. (by Giancarlos)
> Instead of extensions you install, you download a skill file that tells a coding agent how to add a feature. The software stops being an artifact and starts being a living tool that isn't the same as anyone else's copy. I'm curious to see what tooling will emerge for collaborating with this new paradigm.
I build my own inspired by Beads, not quite as you're describing, but I store todo's in a SQLite database (beads used SQLite AND git hooks, I didn't want to be married to git), and I let them sync to and from GitHub Issues, so in theory I can fork a GitHub repo, and have my tool pull down issues from the original repo (havent tried it when its a fork, so that's a new task for the task pile).
https://github.com/Giancarlos/guardrails/issues
You can see me dogfeeding my tool to my tools codebase and having my issues on the github for anyone to see, you can see the closed ones. I do think we will see an increase in local dev tooling that is tried and tested by its own creators, which will yield better purpose driven tooling that is generic enough to be useful to others.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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