
Linear MCP Server
The Linear MCP Server connects Linear’s project management platform with AI assistants and LLMs, empowering teams to automate issue management, search, updates,...
Empower your AI agents and workflows with Linear’s project management features using the Linear MCP Server for automated issue tracking and team collaboration.
The Linear MCP Server is a Model Context Protocol (MCP) server built for seamless integration with the Linear API, enabling AI assistants and agents to interact programmatically with Linear’s issue tracking system. By exposing Linear’s core functionalities via the MCP protocol, this server empowers developers and AI tools to automate and manage project workflows, such as creating, updating, and searching issues, retrieving team information, and managing assignments and comments. The Linear MCP Server acts as a bridge between large language models and the Linear platform, streamlining common developer tasks, supporting enhanced productivity, and fostering efficient collaboration in software projects by facilitating secure, rate-limited, and controlled access to Linear’s data and actions.
No prompt templates are documented in the available resources.
No explicit resources are documented in the available resources.
linear_create_issue
Creates a new Linear issue with specified details. Supports creating sub-issues and assigning labels.
Parameters:
title
(required): Issue titleteam
(required): Team identifier (key, UUID, or name)linear_update_issue
Updates an existing Linear issue with new data (enabled with write access).
linear_search_issues
Searches for Linear issues based on specified criteria.
linear_get_user_issues
Retrieves all issues assigned to a specific user.
linear_get_issue
Fetches detailed information about a specific issue.
linear_get_teams
Retrieves information about teams within Linear.
linear_add_comment
Adds a comment to an existing Linear issue (enabled with write access).
Automated Issue Creation and Management
Developers or AI agents can programmatically create, update, and comment on Linear issues to automate bug tracking, feature requests, and task workflows, improving efficiency and reducing manual overhead.
Personalized Task Retrieval
AI-powered assistants can fetch issues assigned to specific users, helping developers quickly identify and prioritize their work items within Linear.
Project Team Insights
Teams can utilize the server to retrieve and analyze team composition and responsibilities, supporting better project planning and resource allocation.
Integrating Linear with DevOps Workflows
By exposing Linear’s API via MCP, the server enables integration with CI/CD pipelines, chatbots, or dashboards, facilitating real-time project monitoring and automated status updates.
Enhanced Collaboration via AI Assistants
AI assistants can interact with Linear through the MCP server to summarize project status, recommend next actions, or surface relevant issues during team meetings.
No specific instructions or configuration available for Windsurf.
No specific instructions or configuration available for Claude.
No specific instructions or configuration available for Cursor.
Prerequisites:
Installation:
chmod +x linear-mcp-go-*
Set API Key:
export LINEAR_API_KEY=your_linear_api_key
Run Setup:
./linear-mcp-go setup
./linear-mcp-go setup --write-access
./linear-mcp-go setup --auto-approve=allow-read-only
Verify:
{
"mcpServers": {
"linear-mcp-go": {
"command": "./linear-mcp-go",
"args": ["serve"]
}
}
}
To enable write access:
{
"mcpServers": {
"linear-mcp-go": {
"command": "./linear-mcp-go",
"args": ["serve", "--write-access"]
}
}
}
Set your API keys using environment variables:
export LINEAR_API_KEY=your_linear_api_key
Or within the config:
{
"mcpServers": {
"linear-mcp-go": {
"command": "./linear-mcp-go",
"args": ["serve"],
"env": {
"LINEAR_API_KEY": "your_linear_api_key"
}
}
}
}
Using MCP in FlowHunt
To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:
Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:
{
"linear-mcp-go": {
"transport": "streamable_http",
"url": "https://yourmcpserver.example/pathtothemcp/url"
}
}
Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “linear-mcp-go” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.
Section | Availability | Details/Notes |
---|---|---|
Overview | ✅ | |
List of Prompts | ⛔ | No prompt templates documented |
List of Resources | ⛔ | No explicit resources documented |
List of Tools | ✅ | Six tools are listed in README |
Securing API Keys | ✅ | Uses environment variable LINEAR_API_KEY |
Sampling Support (less important in evaluation) | ⛔ | Not documented |
Based on the above, the Linear MCP server is a focused, well-documented integration for Linear workflows, but lacks advanced MCP features such as prompt templates, explicit resource primitives, or sampling/roots documentation. It provides the essentials for developers wanting to automate or enhance their Linear experience via AI assistants.
Has a LICENSE | ⛔ |
---|---|
Has at least one tool | ✅ |
Number of Forks | 4 |
Number of Stars | 8 |
The Linear MCP Server is a bridge between AI agents and the Linear API, exposing project management functions like issue creation, updating, searching, and team management through the Model Context Protocol for automated workflows.
You can automate tasks such as creating and updating issues, retrieving team and user data, managing assignments and comments, and integrating Linear operations into CI/CD pipelines or AI-powered assistants.
Store your API key as an environment variable (e.g., export LINEAR_API_KEY=your_linear_api_key) or within your MCP server config under the env section to prevent accidental exposure.
No, the current implementation focuses on core API actions and does not include prompt templates or explicit resource primitives.
Add the MCP component in your FlowHunt flow, open its configuration panel, and insert your MCP server details in JSON format, specifying the transport and URL for your running Linear MCP instance.
Unlock powerful automation for your Linear projects by connecting the Linear MCP Server with FlowHunt. Streamline your workflow and enhance team productivity today.
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