linear

Official
GitHub Repo

Overview

The linear MCP server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with Linear, the issue tracking and project management platform. It allows AI-driven workflows to create, update, search, and reason about issues, projects, cycles, and teams — bringing planning and execution context directly into AI-assisted development workflows.

This server is especially useful for product planning, engineering management, sprint execution, and triage workflows where Linear is the system of record.

Transport

streamable-http

Tools

  • list_comments
  • create_comment
  • list_cycles
  • get_document
  • list_documents
  • get_issue
  • list_issues
  • create_issue
  • update_issue
  • list_issue_statuses
  • get_issue_status
  • list_issue_labels
  • create_issue_label
  • list_projects
  • get_project
  • create_project
  • update_project
  • list_project_labels
  • list_teams
  • get_team
  • list_users
  • get_user
  • search_documentation

Key Capabilities

  • Issue management — Create, update, and analyze issues programmatically.
  • Project and cycle visibility — Inspect projects, sprints, and planning context.
  • Team awareness — Reason about ownership, assignments, and workflow state.
  • Planning and triage support — Enable AI assistants to help prioritize, summarize, and organize work.
  • Cross-workflow integration — Combine Linear context with code, CI/CD, and observability data in AI-driven workflows.

How It Works

The linear MCP server runs as an MCP service and connects to Linear using an authenticated API token with appropriate scopes. AI clients communicate with the server over the MCP protocol to request issue, project, or team context as part of broader reasoning workflows.

The server mediates access to Linear’s APIs, handling authentication, request execution, and response normalization. Results are returned in structured formats that AI assistants can reason over directly, while respecting Linear’s permission model.

By exposing Linear through MCP, the server enables AI-driven workflows such as backlog review, issue summarization, sprint planning support, and cross-system reasoning — all through natural language and automated reasoning within a single environment.