Linear MCP Server
by argia-andreas
The Linear MCP Server is a Model Context Protocol server designed to facilitate interaction with Linear. It allows AI assistants to fetch data from Linear using the MCP standard.
Last updated: N/A
What is Linear MCP Server?
This server is a Model Context Protocol (MCP) server that enables AI assistants to retrieve data from Linear, a project management tool, through a standardized protocol.
How to use Linear MCP Server?
To use this server, clone the repository, install dependencies using npm install
, configure the .env
file with your Linear API key, and then run the server using npm run dev
for development or npm start
for production. It can be integrated with MCP clients like Claude Code using the provided command.
Key features of Linear MCP Server
Fetches user's todo tickets by user ID or email
Implements the standard MCP protocol
Easy to install and configure
Provides a
get-user-todo-tickets
tool
Use cases of Linear MCP Server
Integrating Linear data into AI assistant workflows
Automating tasks based on Linear ticket status
Providing AI assistants with context from Linear projects
Querying Linear data from conversational interfaces
FAQ from Linear MCP Server
What is an MCP server?
What is an MCP server?
An MCP (Model Context Protocol) server provides a standardized way for AI models and assistants to access data from various sources.
How do I get a Linear API key?
How do I get a Linear API key?
You can obtain your Linear API key from the Linear Developer Console.
What is the get-user-todo-tickets
tool?
What is the get-user-todo-tickets
tool?
This tool retrieves all tickets in the 'Todo' state for a specified user, identified by either their user ID or email address.
Can I use this server with other MCP clients?
Can I use this server with other MCP clients?
Yes, this server implements the standard MCP protocol and can be used with any compatible MCP client.
How do I contribute to this project?
How do I contribute to this project?
Contributions are welcome! Feel free to submit a pull request with your improvements.