How to Use the Linear (Issue Tracking & PM) MCP in Google ADK

Connect your enterprise Gemini agents directly to Linear (Issue Tracking & PM) using the Google ADK.

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Connect Linear (Issue Tracking & PM) MCP to Google ADK

Create your Vinkius account to connect Linear (Issue Tracking & PM) to Google ADK 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 Google ADK

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Perplexity

Analyze project backlogs using Google ADK and Gemini

By calling `list_issues`, your agent pulls hundreds of active tickets straight into Gemini's long-context window. This allows the model to find duplicate work or hidden technical debt across your entire workspace. You can combine this with BigQuery data to cross-reference customer support tickets with engineering tasks. The agent uses `get_issue` to pull granular details on high-priority bugs and updates your database.

Track active sprint cycles automatically

Tracking active sprint cycles is automated when your agent runs `list_cycles` to find boundaries. It calculates sprint velocity and maps out timeline progress without manual intervention. It uses `list_projects` to map active tickets to larger company initiatives. This lets your agent generate clean, data-driven status reports directly inside your enterprise console.

Audit workspace access with this MCP Server

Your agent calls `list_users` and `list_teams` to run security audits on who has workspace access. This keeps your access logs clean and ensures the agent operates within defined security policies. It cross-references this with `get_viewer` to verify its own operational boundaries. It is a straightforward way to maintain strict security controls over your engineering workspace.

Setup guide

Set up Linear (Issue Tracking & PM) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Linear (Issue Tracking & PM) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Linear (Issue Tracking & PM)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Linear (Issue Tracking & PM) tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Linear. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Linear (Issue Tracking & PM) MCP in Google ADK

You install the ADK and configure the toolset pointing to your Vinkius HTTP endpoint. Pass this toolset directly to your agent instance. This gives your Gemini model immediate access to tools like `list_issues` and `list_cycles`.

Yes, you can use the tool names filter parameter in the ADK configuration. This lets you expose only specific tools, like `list_projects`, while hiding administrative tools like `list_users`. It is a great way to enforce the principle of least privilege.

It does, especially when paired with Gemini models. The agent can pull large sets of issues using `list_issues` and analyze them all at once. This makes it easy to spot trends across multiple teams and cycles.

The MCP Server handles basic connection stability, but you should design your agent's prompt to fetch data incrementally. Use `list_teams` first to narrow the scope before pulling issues. This prevents hitting API thresholds during heavy runs.

Your Linear API keys and team profile data are never stored or logged. The Vinkius infrastructure uses ephemeral execution environments to run each tool call. This guarantees that your proprietary code issues and user lists are processed securely and discarded immediately.

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