Linear

MCP server for Linear (https://linear.app), forked from ibraheem4/linear-mcp (https://github.com/ibraheem4/linear-mcp)

javascript

3

GitHub Stars

javascript

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "tiovikram-linear-mcp": {
      "command": "node",
      "args": [
        "/path/to/linear-mcp/build/index.js"
      ],
      "env": {
        "LINEAR_API_KEY": "your-api-key-here"
      }
    }
  }
}

You run a dedicated MCP server that enables AI agents to manage Linear issues, teams, and projects through a simple, programmatic interface. This server exposes a set of actions you can invoke from your agents, allowing you to create, list, and update issues; inspect teams and projects; and filter results to fit your workflow.

How to use

Connect to the MCP server from your client and start issuing tool calls to manage Linear data. You will typically authenticate with an API key and then invoke one of the available actions to create issues, list items with filters, or update records. Use the server as a bridge between your AI agents and Linear’s API, so your agents can operate on issues, teams, and projects as part of automated workflows.

How to install

Prerequisites: you need Node.js v16 or higher and a Linear account with API access.

Install the MCP server locally by running the standard startup command shown in the examples.

LINEAR_API_KEY=your-api-key npx @ibraheem4/linear-mcp

export LINEAR_API_KEY=your-api-key
npx @ibraheem4/linear-mcp

Additional content

Configuration and runtime notes help you tailor the server to your environment and tooling.

Development and local debugging can use an Inspector for interactive tool testing.

The server is built with TypeScript, uses the Linear SDK, and implements the Model Context Protocol for seamless integration with AI agents.

Available tools

create_issue

Creates a new issue in Linear with a title, optional description, team and assignee, and optional priority and labels.

list_issues

Lists issues with optional filters for team, assignee, status, and a limit on number of results.

update_issue

Updates an existing issue with new title, description, status, assignee, or priority.

list_teams

Retrieves all teams in the workspace.

list_projects

Lists all projects with optional filters by team and a limit on results.

get_issue

Retrieves detailed information about a specific issue by its ID.