Superlist MCP vs Todoist MCP vs Linear Agent

Giving an AI assistant access to your tasks sounds efficient right up until it creates duplicate projects, moves the wrong deadline, or turns one messy meeting note into 47 tiny obligations.

That is the real buying question behind Superlist MCP vs Todoist MCP vs Linear Agent. Not "which app has AI?" They all have some AI story now. The better question is: which task system deserves agent access, and which one should stay boring?

My short answer: choose Superlist MCP if you want a fresh AI-readable task layer, choose Todoist MCP if Todoist is already your source of truth, choose Linear Agent if your tasks are product and engineering issues, and choose Super Productivity if you should not connect a cloud assistant to tasks at all.

Does it actually save time or just look cool? For this category, that question is the whole review.

This is an evidence-led comparison. I rechecked the official MCP documentation and pricing pages on August 24, 2026, then recaptured the product evidence shown below. I did not authenticate an MCP connector, connect an AI assistant to a live task account, mutate real tasks, test mobile sync, or measure exact time saved.

If you still need a normal task-manager comparison, start with our Todoist vs TickTick guide. If the problem is calendar ownership, compare the time blocking apps before adding another AI layer. And if your work is team execution rather than personal tasks, the project management tools roundup is the better base layer.

Start with Superlist MCP if you are building the task system around AI access. Use Todoist MCP if migration would create more work than the agent saves. Pick Linear Agent when the task is really an issue, spec, customer request, or bug. Keep Super Productivity in the decision if privacy and local ownership are the point.

If you are choosing the broader AI coworker before its task system, compare Bardeen, Zapier Agents, and Lindy by starting context and approval boundary. This page remains the narrower decision about which task layer deserves agent access.

If the assistant's real job is inbox, calendar, calls, and executive follow-up rather than task-database access, use the AI executive assistant comparison instead.

The task-agent trap

A task system can contain client names, family errands, HR notes, project delays, health reminders, and unfinished thoughts. If a tool turns that into AI context, the buyer needs a reason.

Bad trade: buying an "AI task manager" because the demo looked clean, then spending every Friday deduplicating work the agent created on Tuesday.

Here is my bias: I would rather use a dumb task app I trust than a clever agent I have to babysit. The moment an AI task layer creates a second review queue, it has failed. That is why Super Productivity gets a serious slot here instead of being treated like an odd open-source footnote.

How I ranked the task-agent picks

The rubric has five parts: Agent Access, Workflow Fit, Setup Risk, Pricing Clarity, and Control. Agent Access asks whether the assistant can actually read and update useful task data. Workflow Fit asks whether the app matches personal tasks, AI-assisted list planning, engineering issues, or local deep work. Setup Risk covers OAuth, permissions, connector support, mobile behavior, and the cleanup tax if the assistant touches a messy system. Pricing Clarity asks where the AI and team thresholds actually land. Control asks how much private task context leaves the buyer's device.

Superlist MCP vs Todoist MCP vs Linear Agent

1. Superlist MCP: best AI-first task layer

Superlist MCP wins if you are choosing a task layer for AI on purpose. The official help page says supported assistants can read and update your lists and tasks, and it gives concrete Claude and ChatGPT setup paths through the Superlist MCP URL. Superlist says MCP follows the limits of the connected account rather than adding a separate MCP quota.

That matters because Superlist is not merely adding a smart input box to an old task app. Its pitch is closer to "your lists and notes should be accessible from the conversation where work is already happening." The examples are exactly the tasks an agent should handle: add items, check what is overdue, move unfinished tasks, create a new launch list, summarize the week, or draft a project plan from meeting notes.

The pricing page is also readable. Free allows up to 5 private lists and 5 shared lists with unlimited tasks and notes. Basic is $6/month or $59/year and adds unlimited private lists, sublists, shared lists up to 25 members per list, larger file uploads, 25 GB storage, integrations with Gmail, Google Calendar, Slack, Linear, Email Forwarding, and GitHub, plus Talk AI voice input. Super is $25/month or $249/year and adds unlimited AI meeting notes/summaries, AI chat with meeting notes, AI email/Slack message summarization to tasks, and Make AI content generation. The old $15/month Pro plan is now a legacy plan and cannot be purchased.

The catch is trust. Superlist says the AI tool only gets access to data your account already has access to and that you can revoke access. Good. But a Reddit thread from the Superlist account also surfaced real early-friction examples: Developer Mode tradeoffs, session reconnect issues, and a user wanting better support for task details, reminders, and deadline interpretation. That is not a reason to dismiss it. It is a reason to pilot it on one list before giving it your whole life.

Use it when the task system is still flexible. Do not use it as a cosmetic add-on to a chaotic backlog.

2. Todoist MCP: best if Todoist already runs your life

Todoist MCP is the safest recommendation for existing Todoist users. The current Todoist developer docs list a hosted MCP server, OAuth setup, and support for Claude, ChatGPT, Cursor, and VS Code. The key phrase is full access: read, create, and update your tasks and projects.

That is a big deal because Todoist is not a startup task board trying to find a use case. It already has projects, sections, labels, filters, recurring tasks, reminders, deadlines, comments, files, team workspaces, activity history, and mature clients. If your system is already clean, MCP gives AI access to a structure you trust.

The pricing is less cheap than old Todoist comparisons still suggest. Todoist Pro is $7/month or $60/year, while Todoist Business is $10/user/month or $96/user/year. Ramble’s current limits also matter: Free, Beginner, and Pro Legacy accounts get up to 10 dictation sessions each month, and every dictation counts even if no tasks are added. Pro and Business remove that monthly cap, though Todoist warns that rare rate limits can still apply.

That distinction matters. Ramble solves input friction. MCP grants system authority. One lets you speak a task into Todoist; the other lets an assistant read, create, and update task/project data. Those are not the same risk level.

The reason Todoist is not ranked first is simple: the best Todoist buyer already chose Todoist before MCP entered the room. If you have years of recurring tasks, filters, labels, and team habits there, use Todoist MCP. If you are starting fresh and want an AI-first list layer, Superlist is the cleaner experiment.

3. Linear Agent: best when tasks are product issues

Linear Agent is not a better personal to-do list. It is a better way for software teams to operate around issues, customer requests, specs, triage, code context, and project updates.

The March 2026 Linear Agent launch described an agent grounded in roadmaps, issues, and code, with Automations reserved for Business and Enterprise at launch. The current pricing page is the better guide now: Free includes the Agent platform and Linear Agent, while the feature table lists MCP access, Linear Agent, Coding Sessions, Loops, Code Intelligence, and Triage Intelligence. Coding Sessions and Loops require AI credits.

Pricing tells you who this is for. Linear has a Free plan with unlimited members, two teams, 250 issues, Agent platform, and Linear Agent. Basic is $10/user/month billed yearly, and Business is $16/user/month billed yearly. Business adds unlimited teams, private teams and guests, Triage Intelligence, Loops, Code Intelligence, Linear Insights, Linear Asks, and Zendesk/Intercom integrations.

That is overkill for groceries, daily chores, or solo time blocking. For calendar scheduling, read the Motion vs Reclaim AI comparison. If you are deciding between task and doc workspaces, read ClickUp vs Notion. Linear belongs here because the task-agent question changes when the "task" is an issue with product context attached.

4. Super Productivity: best when AI should stay out

Super Productivity is the boring answer that many buyers should consider first. It is not ranked fourth because it is weak. It is ranked fourth because it does not solve the hosted MCP task-layer problem. Its value is different: every feature and platform is free, there is no account requirement, and the product says task data stays on the device without tracking or sale.

That matters because "let AI manage my task list" is sometimes a symptom of a worse problem: too many tasks, no triage habit, no weekly review, and no place where work is actually trusted. In that case, adding an agent is automation theater.

The main product page adds the workflow details: tasks, time tracking, focus tools, offline/private use, WebDAV or Dropbox sync, and JSON/CSV export. For a developer or freelancer who wants focus sessions, work logs, GitHub/Jira/GitLab import, and privacy, that may be better than connecting yet another cloud service.

How to choose without getting burned

Choose Superlist MCP if the task system is new, flexible, list-heavy, and you want the AI assistant to become part of planning. It is the most interesting fresh option because the product is leaning into the "task layer for agents" idea instead of treating MCP as an appendix.

Choose Todoist MCP if Todoist is already where tasks get trusted. Do not migrate to Superlist just because a launch page looks newer. Migration has a cost, and Todoist now has official hosted MCP. If you already have a clean Todoist system, that is a stronger starting point than a shiny blank board.

Choose Linear Agent if the work is software-team work. Bugs, triage, customer requests, specs, product updates, and code-linked decisions are not normal tasks. They need product context. Linear is built for that context.

Choose Super Productivity if the honest problem is focus, privacy, and ownership. A local-first app will not write your weekly plan from a chat prompt, but it also will not quietly turn half-finished thoughts into cloud agent context.

One hard rule: do not start with full write-access. Start with a low-risk project, read-only summary, or one disposable list. If the assistant cannot keep a clean list clean, it has no business touching the real one.

Pilot checklist before you give an agent write-access

Do the boring pilot first. Create one test project or list with 20-30 real-but-low-risk tasks. Include overdue items, recurring work, vague notes, a few priorities, and one task you definitely do not want changed. Then ask the assistant to summarize the list, identify stale tasks, propose a plan for today, and explain what it would change before it changes anything.

If that read-only pass is useful, allow one narrow write action: add three tasks from a meeting note, move unfinished tasks to tomorrow, or create a project outline from a short brief. Do not test bulk deletion, priority rewrites, or recurring-task edits first. Those are exactly the actions that look efficient in a demo and create cleanup work in a real system.

Check three things after the pilot. First, did the assistant understand your task language, or did it invent its own categories? Second, did the app make permission and undo behavior obvious? Third, did the output reduce work, or did it create a second review queue? If you need to inspect every task like a pull request, the setup is not saving time yet.

That is why I rank Superlist, Todoist, Linear, and Super Productivity as different answers rather than one ladder. The best agent layer is the one that matches the cleanup cost you are willing to own.

Also considered

TickTick is still a strong personal productivity app, especially if calendar and habits matter more than agent access. I did not rank it here because the buying question is MCP/agent task authority, and our Todoist vs TickTick article already covers the normal task-manager decision.

Notion, ClickUp, and Asana can all fit adjacent task and workspace decisions, but they turn this into a broader project-management comparison. For that, use the project management tools guide and then decide whether the AI layer is actually the missing piece.

Zapier, Make, and n8n matter when you want automations between apps instead of AI access to a task database. If your real problem is routing work across tools, the Zapier vs Make vs n8n comparison is more useful than buying another task app.

Final verdict

My default recommendation is Superlist MCP for buyers who want the freshest AI-first task layer, but the wrong buyer can still make it fail. Avoid broad write-access until a pilot proves the agent understands your labels, deadlines, ownership rules, and undo path. The real risk is not the subscription cost; it is giving a confused assistant permission to break the task system your team already relies on.

Most people do not need an AI task manager. They need fewer tasks, cleaner projects, and a weekly review they actually do.

If you already have that discipline, MCP can help. If you do not, it just gives the mess a faster keyboard.