How to Use the Linear (Issue Tracking & PM) MCP in Mastra AI

Build resilient automated workflows for Linear (Issue Tracking & PM) using the Mastra AI engine.

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Connect Linear (Issue Tracking & PM) MCP to Mastra AI

Create your Vinkius account to connect Linear (Issue Tracking & PM) to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Linear (Issue Tracking & PM) with Mastra AI

Ask AI about this MCP

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Claude

Perplexity

Automated issue tracking and cycle management

Set up triggers that fire when a sprint starts. Your workflow uses `list_cycles` to track deadlines and `list_issues` to verify completion. Handle failures by adding logic to retry failed status updates. The agent uses `get_issue` to check the current state before attempting any write operation.

Complex Linear (Issue Tracking & PM) logic with Mastra AI

Create multi-step processes that move tasks between teams. Your agent calls `list_teams` to find the right destination and `list_projects` to confirm the context. Define clear branching paths for your operations. If a project is missing labels, the agent uses `list_labels` to check for missing metadata before flagging an admin.

Auditable workspace activity

Track who changed what in your workspace. Use `get_viewer` to map actions to specific users during your workflow execution. Retrieve full team lists with `list_users` to audit access. This ensures your automated scripts only interact with authorized members of your development environment.

Setup guide

Set up Linear (Issue Tracking & PM) MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Linear (Issue Tracking & PM) tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "linear-issue-tracking-pm-mcp-client",
  servers: {
    "linear-issue-tracking-pm-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Linear (Issue Tracking & PM) Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Linear (Issue Tracking & PM) tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Linear (Issue Tracking & PM) transactions"
);
console.log(result.text);

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Common questions about Linear (Issue Tracking & PM) MCP in Mastra AI

You can define retries for every tool call. If a request to `list_issues` fails due to network issues, the workflow engine handles the backoff automatically.

Absolutely. You import the tools into your agent definition and use them as steps in your automation pipelines.

The server provides the current state of your workspace. Your agent uses that state to decide which path to take next.

You provide your key as an environment variable to the server. It is never logged or exposed outside of your local execution environment.

It reads your issue titles, descriptions, project names, and team memberships. It does not access your personal account settings or payment info.

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