Linear

The Linear agent connector is a Python package that equips AI agents to interact with Linear through strongly typed, well-documented tools. It's ready to use directly in your Python app, in an agent framework, or exposed through an MCP.

Linear is a modern issue tracking and project management tool built for software development teams. This connector provides access to issues, projects, and teams for sprint planning, backlog management, and development workflow analysis.

Example questions

The Linear connector is optimized to handle prompts like these.

• Show me the open issues assigned to my team this week
• List out all projects I'm currently involved in
• List all users in my Linear workspace
• Who is assigned to the most recently updated issue?
• Create a new issue titled 'Fix login bug'
• Update the priority of a recent issue to urgent
• Change the title of a recent issue to 'Updated feature request'
• Add a comment to a recent issue saying 'This is ready for review'
• Update my most recent comment to say 'Revised feedback after testing'
• Create a high priority issue about API performance
• Assign a recent issue to a teammate
• Unassign the current assignee from a recent issue
• Reassign a recent issue from one teammate to another
• Analyze the workload distribution across my development team
• What are the top priority issues in our current sprint?
• Identify the most active projects in our organization right now
• Summarize the recent issues for {team_member} in the last two weeks
• Compare the issue complexity across different teams
• Which projects have the most unresolved issues?
• Give me an overview of my team's current project backlog

Unsupported questions

The Linear connector isn't currently able to handle prompts like these.

• Delete an outdated project from our workspace
• Schedule a sprint planning meeting
• Delete this issue
• Remove a comment from an issue

Installation

uv pip install airbyte-agent-linear

Usage

Connectors can run in open source or hosted mode.

Open source

In open source mode, you provide API credentials directly to the connector.

from airbyte_agent_linear import LinearConnector
from airbyte_agent_linear.models import LinearAuthConfig

connector = LinearConnector(
    auth_config=LinearAuthConfig(
        api_key="<Your Linear API key from Settings > API > Personal API keys>"
    )
)

@agent.tool_plain # assumes you're using Pydantic AI
@LinearConnector.tool_utils
async def linear_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

Hosted

In hosted mode, API credentials are stored securely in Airbyte Cloud. You provide your Airbyte credentials instead.

This example assumes you've already authenticated your connector with Airbyte. See Authentication to learn more about authenticating. If you need a step-by-step guide, see the hosted execution tutorial.

from airbyte_agent_linear import LinearConnector, AirbyteAuthConfig

connector = LinearConnector(
    auth_config=AirbyteAuthConfig(
        external_user_id="<your_external_user_id>",
        airbyte_client_id="<your-client-id>",
        airbyte_client_secret="<your-client-secret>"
    )
)

@agent.tool_plain # assumes you're using Pydantic AI
@LinearConnector.tool_utils
async def linear_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

Full documentation

Entities and actions

This connector supports the following entities and actions. For more details, see this connector's full reference documentation.

Entity	Actions
Issues	List, Get, Create, Update, Search
Projects	List, Get, Search
Teams	List, Get, Search
Users	List, Get, Search
Comments	List, Get, Create, Update, Search

Authentication

For all authentication options, see the connector's authentication documentation.

Linear API docs

See the official Linear API reference.

Version information

• Package version: 0.19.100
• Connector version: 0.1.10
• Generated with Connector SDK commit SHA: 8c602f77c94fa829be7c1e10d063c5234b17dbef
• Changelog: View changelog