This project provides a Model Context Protocol (MCP) server that integrates with the Linear issue tracking system, enabling Large Language Models (LLMs) like Claude Desktop to interact with and manage Linear issues. It targets developers and power users of LLMs who need to automate or augment project management workflows within Linear.

How It Works

The server acts as a bridge, translating LLM requests into actions within Linear via its API. It exposes several tools (linear_create_issue, linear_update_issue, linear_search_issues, linear_get_user_issues, linear_add_comment) that LLMs can invoke. These tools abstract the complexity of the Linear API, allowing LLMs to perform tasks like creating, updating, searching, and commenting on issues using natural language prompts. The MCP standard ensures a consistent interface for LLM interaction.

Quick Start & Requirements

• Installation: npx @smithery/cli install linear-mcp-server --client claude (automatic) or manual setup via claude_desktop_config.json.
• Prerequisites: A Linear API key.
• Setup: Configuration involves adding the server details and API key to Claude Desktop's config file.
• Resources: Linear API Key

Highlighted Details

• Provides tools for creating, updating, searching, and commenting on Linear issues.
• Supports filtering issues by team, status, assignee, labels, and priority.
• Offers specific resource URLs for direct issue, team, user, and organization context.
• Includes example prompts demonstrating LLM interaction with Linear.

Maintenance & Community

The project is maintained by jerhadf. No specific community channels or roadmap links are provided in the README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Permissive license allows for commercial use and integration with closed-source applications.

Limitations & Caveats

The server is designed specifically for integration with Claude Desktop via the MCP. While the core functionality is present, broader LLM framework compatibility or standalone usage is not explicitly detailed.