Linear MCP. Audit issues, sprints, and projects via chat.
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Linear (Issue Tracking & PM) MCP Server lets your AI client manage product development directly from Linear—no clicking necessary. Use natural conversation to retrieve issue contexts, audit sprint cycles, track project boundaries, and view team assignments in real-time.
This tool gives you full control over the entire product lifecycle using only your agent.
What your AI agents can do
Get issue
Retrieves deep context for one specific issue by its ID, giving you full details on that task.
Get viewer
Validates and retrieves active global user boundaries to confirm who has access to what data.
List cycles
Lists the start and end dates for current tracking sprints, so you know when the cycle ends.
Pulls the full context for a specific Linear issue, including its description, priority, and current status.
Retrieves a list of every mapped project in your workspace to define development scope.
Checks the start and end dates for current tracking sprints, allowing you to track time-sensitive progress.
Lists all defined logical teams within your workspace, essential for routing work assignments correctly.
Retrieves a list of active users or validates specific global user boundaries to confirm permissions before actioning anything.
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Linear (Issue Tracking & PM) MCP Server: 8 Tools for Project Auditing
Use these eight tools to retrieve structured data about Linear issues, projects, user boundaries, and sprint cycles directly through your AI agent.
019d75c7get issue
Retrieves deep context for one specific issue by its ID, giving you full details on that task.
019d75c7get viewer
Validates and retrieves active global user boundaries to confirm who has access to what data.
019d75c7list cycles
Lists the start and end dates for current tracking sprints, so you know when the cycle ends.
019d75c7list issues
Provides a list of recent issues mapped in your Linear workspace, giving an overview of what's happening.
019d75c7list labels
Lists all global metadata tags used to categorize issues across the entire project.
019d75c7list projects
Retrieves a list of every active mapped project available in your workspace.
019d75c7list teams
Lists all logical team segment boundaries, which helps route operational assignments accurately.
019d75c7list users
Retrieves a list of all mapped workspace members, validating active access limits for security checks.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Linear (Issue Tracking & PM), then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Linear’s whole damn product lifecycle—you can manage it through natural conversation using your AI agent, so you don't gotta click a single button. You get full control over everything in Linear without ever leaving the chat window.
Getting Context and Scope
Need to know what we're building? You can pull up every mapped project by running list_projects, giving you a clear rundown of the entire scope. If you need an overview of recent work, list_issues gives you a list of all issues currently logged in your workspace. When you wanna deep-dive into one specific task—like checking its description, priority, or current status—you just call up get_issue(id).
This pulls the full context for that single issue.
To keep everything organized and searchable, the system tracks metadata using global tags. You can see every possible tag available across the whole project by running list_labels.
Auditing Time and Teams
Tracking progress means knowing when things are due. To check out sprint cycles, run list_cycles. It tells you exactly what the start and end dates for the current tracking sprints are. For assigning work correctly, you'll need to map team boundaries; calling list_teams gives you a list of all defined logical teams in your workspace, making sure assignments go to the right people.
Managing People and Permissions
Knowing who’s doing what is crucial for keeping things on track. You can check out all mapped workspace members using list_users. Before any action takes place, you should confirm permissions: running get_viewer validates active global user boundaries to make sure your agent knows exactly who has access to which data.
These tools let you audit both the people and the rules governing them.
How Linear MCP Works
- 1 Subscribe to the MCP Server and provide your Linear API Key.
- 2 Ask your AI client for data (e.g., 'List all issues assigned to me in the Engineering team').
- 3 The agent calls the appropriate tools (
list_issues,get_issue, etc.) and formats the structured results into a plain language answer.
The bottom line is: you tell your agent what data you need, and it executes the necessary Linear API calls to get it for you.
Who Is Linear MCP For?
Product Managers who spend too much time hopping between dashboards just to draft a status report. Engineering Leads who constantly have to verify resource allocation across multiple projects. Technical Writers needing to audit the full scope of project labels before documenting a feature release.
Needs to monitor progress and audit sprint cycles using list_cycles and list_issues right before weekly syncs.
Tracks team assignments across multiple projects by calling list_users and cross-referencing with issue distribution.
Discovers global metadata tags using list_labels to ensure all documentation reflects the current internal categorization rules.
What Changes When You Connect
- Know the status without opening a browser. You can pull issue context using
get_issue(id)directly in your agent's response, so you get critical details instantly. - Stop guessing about deadlines. Running
list_cyclesshows exactly when the current sprint ends and how many tasks are left to finish. - Simplify resource checks. Use
list_userscombined withlist_teamsto quickly confirm which team members own specific projects, ensuring no one gets overloaded. - Understand your taxonomy immediately. Running
list_labelsreveals all global metadata tags, so you never assume what a project's categorization rules are. - See everything at once. You can list active projects with
list_projects, giving you a clean scope overview before starting any major audit.
Real-World Use Cases
Need to know who is assigned what?
A new Engineering Lead needs to see the current workload distribution. They ask their agent: 'List all active issues and group them by assignee.' The agent uses list_issues and then iterates through assignments, giving a clean report of capacity across the team.
Checking project scope before kickoff.
A Product Manager wants to start a new feature but needs to know if there are existing overlapping efforts. They run list_projects and cross-reference with list_labels to confirm the project is both active and properly categorized.
Quickly updating an issue status.
A developer finds a bug ticket, 'ENG-101', but needs more context than what's visible. They prompt their agent to get_issue('ENG-101'). The agent returns the full description, priority, and current assignee in one shot.
Auditing team access rights.
The Security Team needs to verify if a new contractor can see data for specific users. They run list_users followed by get_viewer() to confirm the explicit global user boundaries and scope.
The Tradeoffs
Assuming one tool does it all
Trying to get a project's status just by calling list_issues. You only see issues, not the overall project health or scope.
→
First, call list_projects to get the project ID. Then use that ID context with list_issues and potentially get_issue(id) for specific details.
Confusing roles vs. users
Calling list_users thinking it shows team assignments, but it just gives a list of accounts.
→
Use list_teams first to understand the logical groupings. Then use list_issues filtered by those teams for accurate assignment tracking.
Not checking cycle bounds
Starting feature planning on a project without knowing if the sprint has already ended, leading to wasted effort.
→
Always run list_cycles first. This gives you the definitive start and end dates for the current work iteration.
When It Fits, When It Doesn't
Use this MCP Server if your primary need is retrieving structured data about project development, issue status, or team membership from Linear into a conversation thread. The tools are strongest when you pair them: use list_projects to define the scope, then run list_issues for an overview, and finally, call get_issue(id) on any specific ticket that needs deep context. Don't use it if you need to modify data (like changing a status or assignee); this server is built purely for reading and auditing. If your goal involves complex, multi-step data transformation outside of the Linear scope—like connecting issue data to external inventory records—you might need an integration that handles write operations, not just reads.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Linear. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 8 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Checking project status used to be a dashboard maze.
Today, checking if Project X is on track means clicking into the main Linear board, filtering by 'Active', then scrolling through dozens of cards. If you need details on one specific ticket, you click it, open another tab for its labels, and maybe run a search just to confirm who owns it.
With this MCP Server, you simply tell your agent: 'What's the status of Project X?' The agent runs `list_projects` for context, then pulls relevant issues using `list_issues`, giving you a summarized report instantly. You get answers without leaving the chat window.
Using Linear (Issue Tracking & PM) MCP Server: 8 Tools
No more manual data gathering. Instead of opening separate views for project scope, team members, and active sprints, you ask your agent to pull all the metadata in one go—running `list_projects`, then checking `list_teams` for context, and finally auditing with `list_cycles`. All that organizational intelligence is delivered cleanly.
What's different now is control. You stop spending time navigating UIs and start spending time on product decisions. The data comes to you, structured and ready.
Common Questions About Linear MCP
How do I find all issues assigned to a specific team using list_issues? +
The agent can filter the results for you. You just need to ask: 'List all active issues in the Marketing team.' The tool handles running list_issues with the correct team scope.
What is the difference between list_issues and get_issue? +
list_issues gives you a feed of recent tickets—a summary. Use get_issue(id) when you need deep context on one specific ticket, like its full description or priority level.
Can I use list_labels to find out what kind of work is happening? +
Yes. Running list_labels shows every global metadata tag. This helps you understand how the team categorizes different types of work (e.g., 'Bug', 'Feature Request').
How does get_viewer help with security? +
get_viewer() validates your current access rights against global user boundaries. This is useful for confirming that the agent has permission to view certain sensitive data scopes.
If I need to know which users have access to manage my issues, how do I use list_users? +
The list_users tool returns a complete roster of mapped workspace members. It shows their unique IDs and current status within Linear. This helps you validate who has the necessary permissions before attempting an update or assignment through your agent.
What happens if I call get_issue with a project ID that no longer exists? +
The system handles this by returning a specific error code, usually indicating resource not found (404). This means the issue or project identifier you provided is invalid. Your agent can catch this error and prompt you to verify the correct ID.
How do I handle large volumes of data when calling list_projects? +
The list_projects tool supports pagination, meaning it breaks down massive lists into manageable chunks. You'll need to check for a 'next page token' in the response payload to fetch all available projects and avoid hitting rate limits.
Can I use list_cycles to verify if a specific issue is within an active sprint window? +
Yes, list_cycles provides the start and end dates for current tracking sprints. By comparing an issue's creation or due date against these bounds, your agent confirms if the task falls within an active cycle period.
Can I see the full context of a bug report through my agent? +
Yes. Use the get_issue_details tool with a specific Issue ID or UUID. Your agent will retrieve the full description, assigned labels, and current status, helping you understand the technical requirements instantly.
How do I check the progress of the current sprint cycle? +
The list_sprint_cycles tool allows your agent to retrieve current iteration boundaries and temporal limits. You can see which cycles are active and how many issues are assigned to each team grouping.
Can my agent list all members of a specific team in Linear? +
Absolutely. Use the list_workspace_members tool to identify registered users. Your agent will return precise organizational mappings and IDs, making it easy to route assignment requests through natural conversation.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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