Linear alternative for AI coding agents
Linear is a fast issue tracker and can hand issues to AI coding agents. mcptask.online goes one step further: the AI developer (the mcptask runner) runs on a PC or Mac you set aside, with your project, real database and tests, picks the next task from the same queue as your people, and every change ends as a pull request that passes tests and local CI. People and AI developers are users like any other, at the same price.
What Linear does for AI agents today
- You delegate an issue by assigning it to an agent or by @mentioning the agent in a comment or description. Workspace admins install agents and choose which teams they can reach.
- Linear Agent, Linear's own agent, works by default in every workspace. With coding sessions turned on it can be delegated the implementation of an issue.
- A coding session runs in Linear's secure cloud environment, without a local environment on your side. The agent writes and tests the change and returns a draft pull request; your GitHub permissions and review requirements still decide what ships.
- Coding sessions use AI credits and offer a list of Claude, GPT and GLM models, or Claude Code and Codex as the agent. Repositories come through Linear's GitHub integration.
- Third-party agents are app users. Linear does not count them as billable seats.
Linear vs mcptask.online, point by point
Linear's column states only what Linear's own pages say, with the links below the table. “–” means we found no statement either way.
| Linear | mcptask.online | |
|---|---|---|
| Where the AI developer runs | Coding sessions run in a secure cloud environment; no local environment needed | The mcptask runner runs on a PC or Mac you dedicate, with your project cloned, against your real database and tests |
| Who picks the next task | A person delegates an issue (assign it or @mention the agent); Loops run Linear Agent workflows on a schedule or on events | The runner takes the next task from the queue itself: priority, then bugs first, then oldest – the same queue your people work from |
| Tests and CI before merge | The agent writes and tests the change and returns a draft pull request | Code and tests on a branch, then a pull request and local CI on the runner machine |
| Merge | Your GitHub permissions and review requirements decide what ships | In auto-squash modes the runner merges only after green checks; in manual modes the pull request waits for human review |
| Git hosts | GitHub, through Linear's GitHub integration | GitHub, GitLab (including self-managed) and Bitbucket Cloud |
| Model choice | A list of Claude, GPT and GLM models, or Claude Code or Codex as the agent; usage draws on AI credits | The runner drives Claude Code, Codex CLI or OpenCode and is model-agnostic; the AI model is paid to its provider |
| Timesheets | – | AI developers log their work like people do; it lands in the same timesheet and time reports |
| Where the data lives | – | Task management in an EU data centre in the Czech Republic; your database stays on the runner machine |
| Pricing per user | Free $0, Basic $10, Business $16 per user/month billed yearly, Enterprise custom; agents are not billable seats, coding sessions use AI credits | Starter $19/month (min. 2 users), Professional $14 per user/month; people and AI developers are users at the same price |
When Linear is the better choice
- You want a fast, polished issue tracker first, and AI coding is a feature on top of it.
- You prefer the agent to run in a cloud environment and do not want to set aside a machine for it.
- Your code is on GitHub and a draft pull request your team then reviews is all you need from the agent.
- You want to delegate issues to several third-party agents installed in the same workspace.
When mcptask.online fits
- The AI developer has to work against your real database and tests, on a machine you control.
- You want it to pick the next task by itself, in the same order your team would, instead of waiting for someone to delegate each issue.
- Nothing should reach the main branch without tests and local CI – and, in auto-squash modes, green checks.
- Your code lives on GitLab (including self-managed) or Bitbucket Cloud, not only GitHub.
- You bill clients by the hour and need the AI developer's work in the same timesheet as your people.
Moving from Linear
- There is no Linear import. Linking per task exists for Jira, Trello and Easy Redmine; Linear tasks are created again by hand or by an AI assistant through the MCP server.
- You do not have to move everything at once: start with one project and one runner machine, and keep the rest where it is.
- 30 days free, no card needed.
Frequently asked questions
Can Linear assign issues to AI coding agents?
Yes. In Linear you delegate an issue by assigning it to an agent or by @mentioning it, and Linear Agent can take on the implementation in a coding session that runs in Linear's cloud environment and returns a draft pull request.
What does mcptask.online do differently?
The AI developer – the mcptask runner – runs on a PC or Mac you dedicate, against your real database and tests. It takes the next task from the same queue as your people, and every change ends as a pull request that passes tests and local CI.
Can I import my Linear issues?
No, there is no Linear import. Per-task linking exists for Jira, Trello and Easy Redmine. Linear tasks are created again, by hand or by an AI assistant through the MCP server.
Which AI models can the runner use?
The runner drives Claude Code, Codex CLI or OpenCode and is model-agnostic, so the model is your choice. You pay the model to its provider.
How are AI developers priced?
As users, at the same price as people. Starter is for at least two users, Professional is priced per user per month, and both start with 30 days free.