Linear Connector for AI Agents

Give agents tools for secure, real-time access to fetch, search, write, and sync across every system, with replication, entity mapping, and auth built-in.

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About this Connector

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.

CRM

Sales Analytics

Customer Data

project management, issue tracking, engineering productivity

Version Information

Package version

0.19.103

Connector version

0.1.10

SDK commit

cb4380e76ac5cbc67b9089f94522be1bbe9f8d73

Support Open Source

Check us out on Github and join the Airbyte community

Github

Installation & Usage

Get started with the Linear connector in minutes

1

Install Package

Using uv or pip

bash

Copy
uv pip install airbyte-agent-linear

2

Import

Initialize and use

python

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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>"
    )
)

3

Tool

Add tools to your agent

python

Copy
@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 {})

Supported Entities & Actions

Access all your Linear data through a unified API

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| Entity | Actions |\n|--------|---------|\n| Issues | [List](./REFERENCE.md#issues-list), [Get](./REFERENCE.md#issues-get), [Create](./REFERENCE.md#issues-create), [Update](./REFERENCE.md#issues-update), [Search](./REFERENCE.md#issues-search) |\n| Projects | [List](./REFERENCE.md#projects-list), [Get](./REFERENCE.md#projects-get), [Search](./REFERENCE.md#projects-search) |\n| Teams | [List](./REFERENCE.md#teams-list), [Get](./REFERENCE.md#teams-get), [Search](./REFERENCE.md#teams-search) |\n| Users | [List](./REFERENCE.md#users-list), [Get](./REFERENCE.md#users-get), [Search](./REFERENCE.md#users-search) |\n| Comments | [List](./REFERENCE.md#comments-list), [Get](./REFERENCE.md#comments-get), [Create](./REFERENCE.md#comments-create), [Update](./REFERENCE.md#comments-update), [Search](./REFERENCE.md#comments-search) |

Example Prompts

The Linear connector is optimized to handle prompts like these

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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

Why Airbyte for AI Agents?

Built for production AI workloads with enterprise-grade reliability

Agent-Native Design

Structured, LLM-friendly schemas optimized for AI agent consumption with natural language query support.

Secure Authentication

Built-in OAuth 2.0 handling with automatic token refresh. No hard-coded credentials.

Production Ready

Battle-tested connectors with comprehensive error handling, logging, and retry logic.

Open Source

Fully open source under the MIT license. Contribute, customize, and extend freely.

Works with your favorite frameworks

Use the Linear connector with any AI agent framework

🦜

LangChain

🦙

LlamaIndex

🤖

CrewAI

AutoGen

🧠

OpenAI Agents SDK

🔮

Claude Agents SDK

Frequently Asked Questions

Didn't find your answer? Please don't hesitate to reach out.

How do I authenticate with Linear?

The Linear connector supports API key authentication. In open source mode, you provide your Linear API key directly (obtainable from Settings > API > Personal API keys). In hosted mode, credentials are stored securely in Airbyte Cloud and you authenticate using your Airbyte client ID and client secret instead.

Can I use this connector with any AI agent framework?

The connector is compatible with any Python-based AI agent framework including LangChain, LlamaIndex, CrewAI, Pydantic AI, and custom implementations.

Does this connector support write operations?

Yes, the Linear connector supports several write operations. It can create and update issues, create and update comments, and assign or reassign issues to users. However, delete operations (e.g., deleting issues, projects, or comments) and scheduling operations are not currently supported.

How is this different from the Airbyte data connector?

Agent connectors are specifically designed for AI agents and LLM applications. They provide natural language interfaces, optimized response formats, and seamless integration with agent frameworks, unlike traditional ETL-focused connectors.

Will there be a platform for agent connectors?

The hosted version with secure credential storage through Airbyte Cloud is already available. See the hosted usage section in the documentation for setup instructions.

20,000+
community members
6,000+
daily active companies
2PB+
synced/month
900+
contributors