Open-source personal assistants
Self-hostable AI assistants that act on your mail, calendar, docs and chat on your behalf.
Personal assistants here are self-hosted agent platforms that act for you: they browse, read and send mail, edit documents and call third-party APIs, usually from a computer or sandbox of their own. Because they act on real accounts, the code that matters most is not the chat UI but what sits between the model and the side effect. When choosing, check how actions are gated (per-action policy, approval rules, audit trail), where memory and thread history are stored and whether that store is yours, how integrations are reached (MCP, Composio-style catalogues, or custom clients) and where tokens are kept, which model providers and local models are supported, and which external services a deployment cannot run without.
Projects (2)
| Project | Stars |
|---|---|
| CopilotKit/OpenBotSelf-hosted platform where AG-UI agents get their own browser computer, with every action policy-checked and audited first. | ★ 6.1k |
| elie222/rakazoSelf-hosted persistent AI bots on a Pi agent runtime, with Postgres job queue, pluggable sandboxes and rule-based tool approval. | ★ 3.4k |
In the research queue: yc-software/qm.
Comparison questions
Each question is answered separately for every project in this category, from that project's source code.
- How is the assistant architected?Agent loop and runtime; frontend/backend split; main packages; how a user request flows to an action.
- How are integrations (email, calendar, chat, docs) implemented?Which services; API clients vs MCP; OAuth flow; token storage; sync vs on-demand fetch.
- How is memory and user context stored and retrieved?Storage (DB, vector store, files); what is remembered; how it is injected into prompts; summarization.
- How are actions on the user's behalf gated?Approval / human-in-the-loop flows; permission scopes; dry-run or draft modes; audit trail.
- How are LLM providers selected and configured?Supported providers; config surface; tool-calling / structured-output usage; local-model support.
- How is it deployed and self-hosted?Runtime dependencies (DB, queues, browsers); Docker/one-click paths; required external accounts.