Connect AI models and agents to your Linear data securely and programmatically.
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TL;DR - Linear MCP
- Provides a standardized interface for AI models to interact with Linear data.
- Enables AI to find, create, and update Linear issues, projects, and comments.
- Integrates with popular AI clients and development tools like Claude, Cursor, and VS Code.
Pricing: Free forever
Best for: Individuals & startups
Pros & Cons
Pros
- Enables powerful AI automation within Linear workflows
- Offers a standardized and secure way for AI to interact with project data
- Supports a wide range of popular AI clients and development tools
- Provides flexible authentication options including OAuth and API keys
- Centrally hosted and managed, simplifying deployment
Cons
- Requires technical setup and configuration for each integration
- Functionality is currently focused on issues, projects, and comments, with more "on the way"
- Specific client setup instructions vary and may require command-line interaction
Preview
Key Features
Standardized Model Context Protocol (MCP) interfaceSecure access to Linear data for AI modelsAbility to find Linear issues, projects, and commentsAbility to create Linear issues, projects, and commentsAbility to update Linear issues, projects, and commentsOAuth 2.1 with dynamic client registration for authenticationSupport for Streamable HTTP transportsDirect API key and OAuth token authentication
Pricing
Free
Linear MCP is completely free to use with no hidden costs.
What is Linear MCP?
The Model Context Protocol (MCP) server provides a standardized and secure interface for AI models and agents to interact with your Linear data. It allows compatible AI tools to access, create, and update Linear objects such as issues, projects, and comments directly. This server is centrally hosted and managed, adhering to the authenticated remote MCP specification, ensuring secure data exchange.
This tool is designed for developers, AI engineers, and teams leveraging AI to automate or enhance their Linear workflows. By integrating with the MCP server, AI models can become active participants in project management, issue tracking, and team collaboration within Linear, enabling intelligent automation and reducing manual effort. It streamlines the process of bringing AI capabilities into your existing Linear environment.
The MCP server facilitates seamless integration with popular AI clients and development environments, including Claude, Cursor, Codex, Jules, Visual Studio Code, v0 by Vercel, Windsurf, and Zed. It supports various authentication methods, including OAuth 2.1 with dynamic client registration and direct API key/OAuth token usage, offering flexibility for different integration scenarios.
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Linear MCP FAQ
What specific Linear objects can AI models interact with using the MCP server?
AI models can currently find, create, and update issues, projects, and comments within Linear using the MCP server. Additional functionalities are planned for future releases.
How does the MCP server handle authentication for different AI clients and use cases?
The MCP server supports OAuth 2.1 with dynamic client registration for general authentication. For more direct integration, it also allows passing OAuth tokens or API keys directly in the
Authorization: Bearer <yourtoken> header, enabling app user interaction, read-only access, or integration with existing Linear OAuth applications.Can I use the MCP server with an AI tool not explicitly listed in the setup instructions?
Yes, hundreds of other tools that support MCP servers can be configured to use Linear's MCP server. The general settings for these tools involve using 'npx' as the command, '-y mcp-remote https://mcp.linear.app/mcp' as arguments, and no specific environment variables.
What should I do if I encounter an 'internal server error' when trying to connect to the MCP server?
If you receive an 'internal server error', you should first clear any saved authentication information by running
rm -rf ~/.mcp-auth in your Terminal. Additionally, ensure your Node.js version is up to date, as an older version might cause issues.Is the `mcp-remote` module always necessary for clients that don't natively support remote MCP?
Yes, for clients that do not natively support remote MCP, the
mcp-remote module is used to provide backwards compatibility, allowing them to connect to the Linear MCP server.What is the primary benefit of using the Linear MCP server compared to directly integrating with the Linear API?
The MCP server provides a standardized and secure interface specifically designed for AI models and agents, abstracting away some complexities of direct API interaction. It ensures compatibility with a growing ecosystem of AI tools that adhere to the MCP specification, simplifying integration and offering a consistent way for AI to understand and manipulate Linear data.
Source: mcp.linear.app