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
The Jira agent connector is a Python package that equips AI agents to interact with Jira through strongly typed, well-documented tools. It provides access to issues, projects, users, comments, worklogs, and more.
CRM
Sales Analytics
Customer Data
Version Information
Package version
0.1.97
Connector version
1.1.6
SDK commit
cb4380e76ac5cbc67b9089f94522be1bbe9f8d73
Support Open Source
Check us out on Github and join the Airbyte community
Installation & Usage
1
Install Package
Using uv or pip
bash
uv pip install airbyte-agent-jira
2
Import
Initialize and use
python
from airbyte_agent_jira import JiraConnector
from airbyte_agent_jira.models import JiraAuthConfig
connector = JiraConnector(
auth_config=JiraAuthConfig(
username="<Your Atlassian account email address>",
password="<Your Jira API token from https://id.atlassian.com/manage-profile/security/api-tokens>"
)
)3
Tool
Add tools to your agent
python
@agent.tool_plain # assumes you're using Pydantic AI
@JiraConnector.tool_utils
async def jira_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})Supported Entities & Actions
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| Entity | Actions |\n|--------|---------|\n| Issues | [API Search](./REFERENCE.md#issues-api_search), [Create](./REFERENCE.md#issues-create), [Get](./REFERENCE.md#issues-get), [Update](./REFERENCE.md#issues-update), [Delete](./REFERENCE.md#issues-delete), [Search](./REFERENCE.md#issues-search) |\n| Projects | [API Search](./REFERENCE.md#projects-api_search), [Get](./REFERENCE.md#projects-get), [Search](./REFERENCE.md#projects-search) |\n| Users | [Get](./REFERENCE.md#users-get), [List](./REFERENCE.md#users-list), [API Search](./REFERENCE.md#users-api_search), [Search](./REFERENCE.md#users-search) |\n| Issue Fields | [List](./REFERENCE.md#issue-fields-list), [API Search](./REFERENCE.md#issue-fields-api_search), [Search](./REFERENCE.md#issue-fields-search) |\n| Issue Comments | [List](./REFERENCE.md#issue-comments-list), [Create](./REFERENCE.md#issue-comments-create), [Get](./REFERENCE.md#issue-comments-get), [Update](./REFERENCE.md#issue-comments-update), [Delete](./REFERENCE.md#issue-comments-delete), [Search](./REFERENCE.md#issue-comments-search) |\n| Issue Worklogs | [List](./REFERENCE.md#issue-worklogs-list), [Get](./REFERENCE.md#issue-worklogs-get), [Search](./REFERENCE.md#issue-worklogs-search) |\n| Issues Assignee | [Update](./REFERENCE.md#issues-assignee-update) |
Example Prompts
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Show me all open issues in my Jira instance - List recent issues created in the last 7 days - List all projects in my Jira instance - Show me details for the most recently updated issue - List all users in my Jira instance - Show me comments on the most recent issue - Show me worklogs from the last 7 days - Assign a recent issue to a teammate - Unassign a recent issue - Create a new task called 'Sample task' in a project - Create a bug with high priority - Update the summary of a recent issue to 'Updated summary' - Change the priority of a recent issue to high - Add a comment to a recent issue saying 'Please investigate' - Update my most recent comment - Delete a test issue - Remove my most recent comment - What issues are assigned to \{team_member\} this week? - Find all high priority bugs in our current sprint - Show me overdue issues across all projects - What projects have the most issues? - Search for users named \{user_name\}
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
🦜
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.
The Jira connector supports two authentication methods: Open source mode, where you provide your Atlassian account email and a Jira API token directly; and Hosted mode, where credentials are stored securely in Airbyte Cloud and you authenticate using your Airbyte client ID and client secret.
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 Jira connector supports write operations. It can create, update, and delete issues and comments, as well as update issue assignees. Note that time logging and issue transitions are currently unsupported.
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.