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.
About this Connector
Jira is a project management and issue tracking platform used by software development teams. This connector provides access to issues, projects, users, comments, worklogs, and other project data.
CRM
Sales Analytics
Customer Data
Version Information
Package version
0.1.65
Connector version
1.1.3
SDK commit
5b20f488dec0e8f29410823753106603c23a4b65
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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) |\n| Projects | [API Search](./REFERENCE.md#projects-api_search), [Get](./REFERENCE.md#projects-get) |\n| Users | [Get](./REFERENCE.md#users-get), [List](./REFERENCE.md#users-list), [API Search](./REFERENCE.md#users-api_search) |\n| Issue Fields | [List](./REFERENCE.md#issue-fields-list), [API Search](./REFERENCE.md#issue-fields-api_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) |\n| Issue Worklogs | [List](./REFERENCE.md#issue-worklogs-list), [Get](./REFERENCE.md#issue-worklogs-get) |\n| Issues Assignee | [Update](./REFERENCE.md#issues-assignee-update) |
Example Prompts
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Show me all open issues in the \{project_key\} project - What issues are assigned to \{team_member\} this week? - Find all high priority bugs in our current sprint - Get the details of issue \{issue_key\} - List all issues created in the last 7 days - Show me overdue issues across all projects - List all projects in my Jira instance - Get details of the \{project_key\} project - What projects have the most issues? - Who are all the users in my Jira instance? - Search for users named \{user_name\} - Get details of user \{team_member\} - Show me all comments on issue \{issue_key\} - How much time has been logged on issue \{issue_key\}? - List all worklogs for \{issue_key\} this month - Assign \{issue_key\} to \{team_member\} - Unassign \{issue_key\} - Create a new task in the \{project_key\} project called '\{issue_title\}' - Create a bug in \{project_key\} with high priority - Update the summary of \{issue_key\} to '\{new_summary\}' - Change the priority of \{issue_key\} to high - Add a comment to \{issue_key\} saying '\{comment_text\}' - Update my comment on \{issue_key\} - Delete the test issue \{issue_key\} - Remove my comment from \{issue_key\}
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 API token authentication. You need to provide your Atlassian account email address as the username and a Jira API token (generated from https://id.atlassian.com/manage-profile/security/api-tokens) as the password.
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 including creating issues, updating issues, deleting issues, assigning issues, creating and updating comments, and deleting comments. However, some write operations like logging time and transitioning issues 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.
