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Freemium
Developers integrating AI agents into task workflows
Lucidos
FreeOpen SourceAPISelf-HostedAgentic
Every vibe-coded app you build ends up as its own island — its own repo, its own keys, its own copy of your data — and by the twentieth one, the maintenance cost has swallowed the productivity gain. Lucidos exists to give everything you describe a single home that keeps running without you.
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Get This Tool
License: MIT Any use incl. commercial
Local-run terms: Build from source or use provided installers; full source available under MIT; run on your machine with your data and LLM keys.
Pricing
- Model
- Free
Summary
Lucidos is a self-hosted, MIT-licensed AI OS that builds apps, dashboards, and automations from plain-language descriptions and runs them persistently on your own machine. You describe what you want — a half-marathon tracker, a language coach, a weekly digest from three APIs — and Lucidos writes it, wires it to your data, and keeps it alive without a separate deploy step. Shared long-term memory means every app and automation you add already knows your context, so complexity compounds instead of restarting at zero. The stack is Rust engine, TypeScript frontend, and a Postgres event store, so self-hosting is real infrastructure, not a checkbox. Where it breaks: the tool is early-stage and community-built, so production reliability for event-driven automations calling external APIs depends heavily on your own debugging tolerance.
Bottom line: Reach for Lucidos when you want a single local workspace that compounds your personal tooling over time — but plan for manual troubleshooting when an event-driven automation silently stops firing against a third-party API at 2 a.m.
Find your fit
Before you choose Lucidos
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Pros
- Shared long-term memory across all apps and automations, so you define your context once and every tool you build afterward inherits it — no more re-entering who you are and what you're working on into each new thing you create.
- Persistent local execution with your own LLM keys, so your data never touches a vendor's servers and API cost is under your direct control rather than buried in a SaaS margin.
- Event-driven automations that react to external services and run on a schedule, so the software does the work while you're not watching instead of waiting for you to trigger it manually.
- MIT licensed with a Rust/TypeScript/Postgres stack and a documented build-from-source path, so you can inspect, modify, and extend everything rather than being gated by a vendor's feature roadmap.
- Single workspace across desktop and mobile with no separate deploy step, so an app you describe on your laptop is immediately available on your phone without publishing anything.
Cons
- Event-driven automations that call external APIs run on your local machine, which means the moment your machine sleeps, reboots, or loses network, the automation stops with no managed fallback — teams running anything time-critical discover this the first time a nightly report silently fails to fire.
- There is no multi-user or team access model described anywhere in the documentation; the workspace is single-user by design, so the moment a second person needs to share an automation or co-edit a dashboard, the architecture has no answer and teams move to a hosted multi-tenant platform instead.
- The tool is early-stage and community-maintained under MIT, which means debugging a broken automation that calls a third-party API requires reading Rust logs and Postgres event tables yourself — there is no support tier to escalate to, and teams with low debugging tolerance abandon it for a managed no-code alternative after the first non-obvious failure.
About
- Platforms
- Mac (Apple Silicon), Linux, mobile
- API Available
- Yes
- Self-Hosted
- Yes
- Last Updated
- August 14, 2026
Best For
Who it's for
- Users wanting a single persistent local workspace for AI-built tools
- Developers and power users creating hyper-specialized personal apps
- Anyone avoiding scattered apps, repos, and credential duplication
- Those preferring local execution with their own LLM keys
What it does well
- Build custom trackers, dashboards, and weekly reports from descriptions
- Create personal coaches or language lesson automations
- Set up event-driven automations that act on external services
- Maintain persistent workspace with shared memory across apps and chats
- Integrate multiple data sources and services into unified tools
Integrations
Frequently Asked Questions
- Is Lucidos free?
- Lucidos offers a free option. Hosting, model usage, or optional services may have separate costs; check the pricing details and official terms.
- Is Lucidos open source?
- Yes. Lucidos is open source.
- Does Lucidos have an API?
- Yes. Lucidos exposes a developer API. See the official documentation at https://lucidos.dev for details.
- Can I self-host Lucidos?
- Yes. Lucidos supports self-hosting on your own infrastructure.
- What platforms does Lucidos support?
- Lucidos is available on: Mac (Apple Silicon), Linux, mobile.
Curated lists that include this category
Scattered apps erode their own gains
Every vibe-coded app you build ends up as its own island — its own repo, its own keys, its own copy of your data — and by the twentieth one, the maintenance cost has swallowed the productivity gain. Lucidos gives every described tool a single home that keeps running without a separate deploy step.
Core capabilities
The vendor describes Lucidos as a self-hosted, MIT-licensed AI OS that builds apps, dashboards, and automations from plain-language descriptions. It runs them persistently on your machine using a Rust engine, TypeScript frontend, and Postgres event store. Shared long-term memory lets each new app inherit context from prior ones. Event-driven automations react to external services on a schedule. The tool lists support for Mac (Apple Silicon), Linux, and mobile, plus integrations with external APIs, email, files, Claude, OpenAI, and local LLMs. It offers an API and is free.
Trade-offs
Automations stop when the local machine sleeps or loses network, with no managed fallback. The workspace is single-user by design, so teams needing shared access must look elsewhere. The docs describe no multi-user model.
Who it is for / who should skip it
Best for users wanting a single persistent local workspace for AI-built tools, developers creating hyper-specialized personal apps, and anyone avoiding scattered repos and credential duplication. Those preferring local execution with their own LLM keys will find it fits. Skip it if you need reliable always-on automations or multi-user collaboration.
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