Atlarix
Summary
Most AI coding tools route your code through their servers by default, leaving privacy-conscious teams to choose between capability and compliance — Atlarix is built around the opposite assumption, keeping code on your machine with every proposed change sitting in an approval queue before it lands.
Atlarix is a desktop AI workstation where agents plan, write, test, and debug inside workspaces you control, with a full terminal, an integrated browser the agent can drive, and a visual map of your codebase that updates as things change. You can run managed models, plug in your own API keys, or run models entirely locally — the vendor states code stays on your machine regardless of which path you choose. The approval queue is the core safety mechanism: nothing ships until you accept the diff. Parallel workers let the agent split a task into up to five concurrent efforts, each reporting back independently. The separate Reviewer product reads pull requests on GitHub and posts line-level findings without ever writing to or executing your code.
Bottom line: Pick Atlarix when your team needs local-first AI coding with an auditable approval layer — plan a different architecture if you need a public API to embed these capabilities in your own product, since no API is available.
Pricing Plans
Subscription- Price
- $19/month
- Free Tier
- 1 workspace; pay-as-you-go credits from the start; limited MCP servers, automations, skills
Free
1 workspace, pay-as-you-go credits, own API keys/local models, 1 MCP server, 2 automations, 3 skills
- 1 workspace
- Pay-as-you-go credits
- Own API keys/local models
Pro
Unlimited workspaces, Atlarix Core for everyday work then pay-as-you-go, 10 MCP servers, 10 automations, unlimited skills + marketplace, OAuth connectors, full parallel workers
- Unlimited workspaces
- Marketplaces
- OAuth connectors
Reviewer
GitHub App for unlimited PR reviews, $19 per developer per month, separate from Pro
- Unlimited repositories
- Unlimited pull requests
View full pricing on atlarix.dev →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Local-first model execution with bring-your-own-key and fully local options, so your source code never leaves the machine — which means teams under data residency or IP constraints do not have to choose between AI assistance and compliance.
- Per-diff approval queue on every agent action, so no generated code reaches your repository without a human reviewing the exact change — which prevents the silent rewrites that make agent-generated code hard to audit after the fact.
- Up to five parallel workers on a single task, so the agent can explore multiple approaches simultaneously and report back, rather than forcing you to wait on a sequential chain that fails at step three.
- Persistent terminal and agent-driven browser in the same session, so the agent can run your app, hit a live endpoint, and read what comes back — rather than generating code it has never executed against your actual environment.
- Separate Reviewer product posts line-level PR findings with suggested fixes without writing to or running your code, so teams get a second pass on every pull request without granting the tool write access to the repository.
Cons
Sign in to edit- No public API is available, so teams that need to trigger Atlarix agents from CI pipelines, internal tooling, or other products have no programmatic path — at that wall, teams move to tools like Cursor or Continue that expose an API or extension surface.
- The parallel worker ceiling of five concurrent efforts is a hard architectural limit the vendor states on the page — large monorepo tasks that benefit from broader parallelism require breaking work into manually sequenced sessions, which erodes the time advantage the parallel model is supposed to provide.
- The Reviewer product is a paid-only feature and installs as a separate GitHub App — teams expecting a single unified product discover late that PR review is a distinct purchase and integration step, not a toggle in the main workspace.
About
- Platforms
- macOS, Linux, Windows
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- 2026-08-28T08:01:41.194Z
Best For
Who it's for
- Engineering teams needing private/local AI coding assistance
- Users wanting approval queues and workspace management
- Teams integrating with Git, GitHub/GitLab, and databases via terminal
What it does well
- Code planning, building, reviewing, testing, and refining in workspaces
- Running local models or own API keys without sending code to cloud
- Automating tasks with MCP servers and skills in engineering workflows
- Reviewing pull requests via separate GitHub App integration
Integrations
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Compare Atlarix
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Sign Up to ContributeFrequently Asked Questions
- Is Atlarix free?
- Atlarix has a permanent free tier alongside paid upgrades (paid plans from $19/month). You can keep using a baseline version indefinitely without paying.
- Is Atlarix open source?
- No — Atlarix is a closed-source tool. Source code is not publicly available.
- Can I self-host Atlarix?
- Yes. Atlarix supports self-hosting on your own infrastructure.
- What platforms does Atlarix support?
- Atlarix is available on: macOS, Linux, Windows.
Curated lists that include this category
Server-side code routing creates compliance headaches
Most AI coding tools route your code through their servers by default, leaving privacy-conscious teams to choose between capability and compliance — Atlarix is built around the opposite assumption, keeping code on your machine with every proposed change sitting in an approval queue before it lands.
Workspaces and agent controls
Atlarix is a desktop AI workstation where agents plan, write, test, and debug inside workspaces you control, with a full terminal, an integrated browser the agent can drive, and a visual map of your codebase that updates as things change. You can run managed models, plug in your own API keys, or run models entirely locally — the vendor states code stays on your machine regardless of which path you choose. Parallel workers let the agent split a task into up to five concurrent efforts, each reporting back.
Safety and pricing
The approval queue is the core safety mechanism: nothing ships until you accept the diff. It runs on macOS, Linux, and Windows at $19 per month on a subscription model, with a free tier limited to one workspace, pay-as-you-go credits from the start, and restricted MCP servers, automations, and skills. Integrations include Slack, Jira, Linear, Notion, Git, GitHub, GitLab, and PostgreSQL. A self-hosted option exists.
Trade-offs
Local-first model execution with bring-your-own-key and fully local options means source code never leaves the machine, so teams under data residency or IP constraints do not have to choose between AI assistance and compliance. The per-diff approval queue prevents silent rewrites that make agent-generated code hard to audit. No public API is available, so teams needing to trigger agents from CI pipelines have no programmatic path. The parallel worker ceiling of five is a hard limit for large monorepo tasks.
Who it is for / who should skip it
Best for engineering teams needing private or local AI coding assistance, users wanting approval queues and workspace management, and teams integrating with Git, GitHub, GitLab, and databases via terminal. Skip it if you require a public API or more than five concurrent parallel workers.