by pmndrs
Open-source agent daemon whose agents wake on events, schedules and chat
Choose Pine if you run macOS or Linux with Node 24 and want agents that react to events and schedules instead of waiting for chat. It is still a 0.x release with breaking changes between versions and a very small community, so it suits tinkerers, not teams that need support.
Agents are woken by events and schedules, not only by chat, inside an OS sandbox.
The pmndrs name and an event-first design set it apart, but a two-day-old project with no hosted tier has little lock-in and rivals can copy the idea.
Main trade-off
Very new, macOS and Linux only, with breaking changes between releases.
Free and open source under the MIT licence, with no paid plan or hosted version found. You pay your model provider, whether a Claude or ChatGPT subscription, a hosted API or your own hardware for a local model server.
| System | Type |
|---|---|
| Telegram | Native |
| MQTT | Native |
| Model Context Protocol servers | Plugin |
| Webhooks | Webhook |
Pine is an MIT-licensed, event-driven multi-agent daemon with a terminal UI from the pmndrs collective, first published on 10 November 2026. Agents wake on events such as new files, Telegram messages, MQTT topics and webhooks, run inside an operating-system sandbox, and use MCP servers, skills and sub-agents with whichever model you connect.
Event-driven agents
Agents subscribe to sources in the real world and on the network, and wake when something happens there, with no chat message needed.
Schedules with a task
An agent can be woken by cron, every-so-often or one-off schedules that carry a task.
Set up by asking
Agents add MCP servers, skills, sources and schedules through tool calls, so there are no configuration files to edit by hand.
Sandbox and three modes
Shell and file tools run in an OS sandbox, and each agent is in manual, auto or bypass mode, from approving every change to checking nothing.
Delegation and sub-agents
The main agent creates other agents, hands them work, and starts parallel sub-agents with their own prompts.
Terminal UI like a desktop app
Tabs, buttons, inline images and video, and drag-and-drop with thumbnails, on Kitty-protocol terminals such as Ghostty.
Self-discovery manual
A built-in search tool lets an agent look up how pine works on demand instead of carrying the docs in its context.
| Agent | Where it runs | Price | Maturity | Rating |
|---|---|---|---|---|
| Pine This page | Your machine | Free | Beta | 3.3 |
| Cloud · Your machine · API | Free | Beta | -- | |
| Cloud · Your machine · API | Free plan | Available | 3.7 | |
| Your machine | Free | Available | -- |
Pine itself is free: it is released under the MIT licence and installs with one npm command. The cost comes from the model you connect, which can be a Claude or ChatGPT subscription, a hosted provider such as OpenCode Go, or a local llama-server that costs only your own hardware. Hokai found no paid Pine plan, hosted version or usage fee in the repository or its docs.
Yes, the source is public on GitHub under the MIT licence and there is no paid tier. You need Node 24 or newer, macOS or Linux, and a model that supports tool calls. On Linux the agent sandbox needs bubblewrap, and without it agents get no shell.
Each agent runs in one of three modes. The default, auto, asks almost nothing: only your approve list asks, and after an agent reads outside content a second model call, the reviewer, checks actions that send, reach out or change its memory. Manual mode waits for you on every change, and bypass checks nothing.
Run pine login with a provider, for example pine login anthropic or pine login openai-codex for a Claude or ChatGPT subscription, or pine login opencode-go, then choose the model with /model in the UI. A model server of your own is added by a command or by the main agent, with its key read from the .env file, and the docs say to start a local llama-server with tool-call support.
Agents subscribe to event sources: Telegram, MQTT, watched folders, webhooks, FTP uploads, polled web addresses and repeated commands. Schedules can also wake an agent by cron, interval or at one set time. An agent sets a source up when you ask it, and only the main agent can add a new kind of source.
Pine is an open-source, event-driven agent daemon from the pmndrs collective, first published on GitHub on 10 November 2026. Its README sums it up as "React for AI": instead of waiting for a chat message, an agent subscribes to things that happen elsewhere, such as a new file in a folder, a Telegram message, an MQTT topic, a webhook or a changed web page, and then acts. That always-on loop of waking, planning and using tools is the difference from a chat tool. It is built on the pi coding agent SDK and drives agents from a terminal UI or from Telegram.
Pine brings no model of its own. You sign in to a provider with pine login, for example a Claude or ChatGPT subscription, or point it at a local llama-server, then pick the model in the UI. Agents run shell and file tools inside an operating-system sandbox (Apple's sandbox-exec on macOS, bubblewrap on Linux), and each agent has a mode that decides how much it does without asking. Tools, MCP servers, skills and schedules are set up by asking an agent in plain language, not by editing configuration files.
It fits people who want a home or work automation layer: watching a folder of scanned documents, reacting to a device on an MQTT broker, running coding sessions with a git diff pane, or splitting a job across sub-agents and pinned tabs. Models it can use include Claude and ChatGPT through their subscriptions.
Pine is the wrong pick for Windows users, since the README says only Docker is offered there, and for teams that need vendor support or a long track record. A self-hosted gateway behind your chat apps is OpenClaw. A coding agent for the terminal, desktop and IDE is OpenCode, whose Hokai record cites 208K GitHub stars. A model-agnostic agent with a far larger community is Hermes Agent, whose Hokai record cites past 260,000 stars against Pine's 50 on 12 November 2026. One Docker container per session is NanoClaw. The wider field is in personal assistant agents.
Autonomy, guardrails, integrations and pricing on this page are read from pmndrs's own documentation. The verdict is Hokai's reading of them, not the vendor's claim.