Linear Issue Management
STDIOProvides Linear integration capabilities through MCP for issue tracking and project management.
Provides Linear integration capabilities through MCP for issue tracking and project management.
This server provides Linear integration capabilities through the Model Context Protocol (MCP). It allows AI models to interact with Linear for issue tracking and project management.
The server provides the following tools through the MCP interface:
Creates a new Linear issue with the following parameters:
title
(required): Issue titleteamId
(required): Team ID to create issue indescription
(optional): Issue description (markdown supported)priority
(optional): Priority level (0-4)status
(optional): Initial status nameSearch Linear issues with flexible filtering and pagination support:
query
(optional): Text to search in title/descriptionteamId
(optional): Filter by teamstatus
(optional): Filter by statusassigneeId
(optional): Filter by assigneepriority
(optional): Priority level (0-4)limit
(optional, default: 10): Max results per pagecursor
(optional): Pagination cursor for fetching next pagesortBy
(optional, default: 'updated'): Field to sort by ('created', 'updated', 'priority', 'title')sortDirection
(optional, default: 'desc'): Sort direction ('asc', 'desc')Get all issues in the current sprint/iteration:
teamId
(required): Team ID to get sprint issues forSearch and retrieve Linear teams:
query
(optional): Text to search in team namesFilter current sprint issues by status and automatically filters to the current user:
teamId
(required): Team ID to get sprint issues forstatus
(required): Status to filter by (e.g. "Pending Prod Release")Get detailed information about a specific issue, including full description, comments, and metadata:
issueId
(required): Issue ID (e.g., "DATA-1284") to fetch details forUpdate the status of multiple Linear issues at once:
issueIds
(required): List of issue IDs to update (e.g. ["ENG-123", "DATA-456"])targetStatus
(required): Target status to set for all issues (e.g. "In Progress")Create, update, or get information about Linear cycles (sprints):
action
(required): Action to perform: "create", "update", "get", or "list"teamId
(required): Team ID to manage cycles forcycleId
(optional, required for update and get actions): Cycle IDname
(optional, required for create): Cycle namestartDate
(optional, required for create): Start date in ISO format (YYYY-MM-DD)endDate
(optional, required for create): End date in ISO format (YYYY-MM-DD)description
(optional): Cycle description.env
file in the project root:LINEAR_API_KEY=your_api_key_here
npm install
# Development mode with auto-reload npm run dev # Production mode npm start # Build TypeScript npm run build # Run linter npm run lint # Run tests npm run test # Inspect MCP server npm run inspect
The server includes comprehensive features for performance and reliability:
@linear/sdk
: Linear API client@modelcontextprotocol/sdk
: MCP server implementationzod
: Runtime type checking and validationdotenv
: Environment variable managementFor the complete list of dependencies, see package.json
.
This server can be deployed on Smithery.ai using the provided configuration files:
The repository includes two essential files for Smithery deployment:
Dockerfile: Defines the server build process
smithery.yaml: Defines the server startup configuration
You can test the Smithery configuration locally using the MCP Inspector:
# Build the Docker image docker build -t linear-mcp-server . # Run the container with your Linear API key docker run -e LINEAR_API_KEY=your_api_key_here linear-mcp-server # Or use the MCP Inspector npm run inspect