This JIRA MCP server implementation, developed in Python, provides a bridge between AI assistants and JIRA's project management capabilities. Leveraging libraries like jira, mcp-server, and pydantic, it offers tools for issue tracking, project management, and workflow automation. The implementation focuses on simplifying interactions with JIRA's API, making it accessible for AI models to create, update, and query issues, manage projects, and automate workflows. It's particularly useful for tasks like automated bug tracking, sprint planning, or integrating project management into AI-driven systems, enabling assistants to interact with JIRA without requiring deep knowledge of the underlying API complexities.
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Delete a Jira issue or subtask using its issue key.
Create a new Jira issue with customizable fields including summary, description, type, priority, and assignee.
Retrieve complete issue details including comments and attachments for a given issue key.
Download an attachment from a Jira issue to a local file.
Create relationships between issues (e.g., 'blocks', 'is blocked by', etc.).
Update existing issues with new values for fields like summary, description, status, priority, or assignee.
Look up a user's account ID using their email address.
Get a list of all available JIRA fields and their properties.
Retrieve all available issue types in your JIRA instance.
Get all possible relationship types for issue linking.
Search for issues using JQL (JIRA Query Language) within a specific project.
Add a text comment to an existing issue.
Add a comment to an issue with an attached file.
Add a file attachment to an existing issue.
Create and attach content directly to a Jira issue (allows creating attachments from any text or data content).
