mcp-server-linear MCP Server: Data Integration for Linear

Overview: What is mcp-server-linear MCP Server?

The mcp-server-linear is an MCP (Model Context Protocol) server designed to seamlessly integrate with Linear, a project management tool. This server bridges the gap between AI applications such as Claude Desktop, Continue, and Cursor, by offering a standardized API for these applications to interact with Linear's rich feature set.

🔧 Core Features & MCP Capabilities

The mcp-server-linear serves as an essential component in the broader MCP ecosystem. It provides several core features that make it highly valuable for AI applications:

Search Issues: The linear-search-issues tool allows AI applications to search for specific issues within Linear, providing a powerful way to gather and analyze data.
Create & Update Issues: Users can leverage the linear-create-issue, linear-update-issue, and linear-get-issue tools to manage issues directly from their AI application.
Issue and Project Interactions: By leveraging linear-get-project-issues, linear-add-comment, linear-create-project, and linear-update-project, developers can enhance user interactions within Linear, making it easier to track tasks and collaborate.

⚙️ MCP Architecture & Protocol Implementation

Technical Details of the MCP Protocol Flow

The mcp-server-linear implements the MCP protocol through a series of HTTP endpoints that are compatible with both Node.js and Bun. The implementation ensures seamless communication between AI applications, the MCP client, and the Linear server.

Mermaid Diagram: MCP Protocol Flow

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Mermaid Diagram: Data Architecture

graph TD;
   G[data] --> H[input-transform]
   H[input-transform] --> I[MCP Handler]
   I[MCP Handler] --> J[Linear API]
   J[Linear API] --> K[Data Source / Tool]
   style G fill:#e5f5d8
   style H fill:#fff7c8
   style I fill:#a6df97
   style J fill:#b4eaff
   style K fill:#f0ede3

🚀 Getting Started with Installation

Bun Runtime

To run the mcp-server-linear using Bun, install the server and execute the following command:

bun run index.ts

This setup enables developers to quickly deploy the server directly from their development environment.

Node Runtime

Alternatively, users can opt for the traditional Node.js runtime. Use the following command to run the server:

node build/index.js

💡 Key Use Cases in AI Workflows

The mcp-server-linear is particularly useful in scenarios where AI applications require real-time data interaction with Linear. For example, an AI-driven ticket management system can use this server to automatically update tickets based on user interactions.

Real-world Implementation 1: Ticket Management System

Imagine a scenario where users manage software development tickets through their AI application. The mcp-server-linear can be integrated into the backend of such a system by using tools like linear-create-issue, allowing developers to create new issues directly from the UI. This not only streamlines the workflow but also ensures consistent data integrity.

Real-world Implementation 2: Project Collaboration

In another scenario, project managers might want their AI application to automatically update project statuses and task assignments at regular intervals. By utilizing linear-update-project and linear-get-issue, the server can provide real-time updates to Linear projects, enhancing team collaboration and visibility.

🔌 Integration with MCP Clients

The configuration details for integrating mcp-server-linear into your system are provided below. These configurations work seamlessly regardless of whether you're using Bun or Node.js as your runtime environment.

JSON Configuration Example (Bun Runtime)

"linear": {
  "command": "bun",
  "args": [
    "run",
    "/path/to/linear-mcp-server/index.ts"
  ],
  "env": {
    "LINEAR_API_KEY": "lin_api_ABCD"
  }
}

JSON Configuration Example (Node Runtime)

"linear": {
  "command": "node",
  "args": [
    "/path/to/linear-mcp-server/build/index.js"
  ],
  "env": {
    "LINEAR_API_KEY": "lin_api_ABCD"
  }
}

JSON Configuration Example (Standalone Executable)

"linear": {
  "command": "/path/to/linear-mcp-server/standalone-linear-mcp-server",
  "args": [],
  "env": {
    "LINEAR_API_KEY": "lin_api_ABCD"
  }
}

📊 Performance & Compatibility Matrix

The compatibility matrix below showcases the status and capabilities of mcp-server-linear with various AI applications:

MCP Client	Resources	Tools (Issues)	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🛠️ Advanced Configuration & Security

For advanced users, there are several configuration options to fine-tune the server for specific use cases. These include setting environment variables and adjusting API endpoints.

Environment Variables

Use environment variables such as LINEAR_API_KEY to secure your application settings. This ensures that critical access keys are not exposed in code repositories or logs.

❓ Frequently Asked Questions (FAQ)

How do I integrate my AI application with mcp-server-linear? Follow the JSON configuration examples provided to integrate mcp-server-linear into your MCP client setup.
Can I use both Node.js and Bun runtimes for this server? Yes, you can choose between Bun or Node.js, depending on your deployment preferences.
What tools are supported by the mcp-server-linear configuration? The currently supported tools include searching, creating, updating issues, adding comments, and managing projects in Linear.
Can I use this server with AI applications that don’t support MCP yet? While primarily optimized for MCP-compatible AI applications, it is possible to extend or modify the server's capabilities to fit other needs on a case-by-case basis.
Is there any additional documentation available for advanced users? Yes, detailed guides and configuration options are provided in the development and contribution guidelines section.

👨‍💻 Development & Contribution Guidelines

Contributions to mcp-server-linear are encouraged from the community. Developers can contribute by adding new tools, reporting issues, or improving existing ones. Contributions should follow the guidelines for pull requests and code quality standards.

🌐 MCP Ecosystem & Resources

Explore more about the MCP ecosystem and related resources:

By leveraging mcp-server-linear, developers can enhance their AI applications with powerful integrations, streamlining workflows and improving productivity.

mcp-server-linear