Jira MCP for Engineering Teams
Let AI agents manage sprints, triage issues, generate engineering reports, and automate backlog grooming — directly in Jira with full enterprise governance.
Engineering teams spend hours in Jira managing sprint ceremonies, writing issue descriptions, updating ticket statuses, and generating progress reports. With Willow's governed Jira MCP server, AI agents can handle these mechanical tasks — creating tickets from requirements, generating sprint reports, triaging incoming issues, and keeping your backlog healthy — all with the SSO and audit controls enterprise engineering organizations require.
How It Works
Connect Jira via Willow
Install Willow's Jira MCP server. Configure project and issue type access. Authentication flows through your existing SSO.
AI Agent Works Your Backlog
Your AI agent reads sprint data, issue details, comments, and project metadata — then creates, updates, or triages issues based on your instructions.
Automate Engineering Workflows
Generate sprint reports, create tickets from PRDs, triage bug reports, estimate story points, and run retrospective summaries — all through natural language.
Governed Access at Every Step
Every Jira operation is logged. RBAC ensures agents only access the projects they're permitted to — no cross-project data leakage.
What You Can Build
Sprint Report Generation
Automatically generate sprint completion reports including velocity, completed stories, carry-over work, and blocker analysis.
Example prompt
“Generate a sprint report for Sprint 42 in the Platform team project. Include completed stories, carry-over tickets, velocity vs. average, and any recurring blockers.”
Issue Creation from Requirements
Convert product requirements documents into structured Jira epics, stories, and subtasks — complete with acceptance criteria, story points estimates, and labels.
Example prompt
“Create Jira stories from this PRD section. Break it into epics and stories, add acceptance criteria, and estimate story points based on our historical velocity.”
Bug Triage Automation
Classify incoming bug reports by severity, affected component, and team ownership — auto-routing P0/P1 bugs to the right team's sprint.
Backlog Grooming
Analyze the backlog for stale tickets, duplicates, unclear requirements, and missing acceptance criteria — surface items needing attention before sprint planning.
Example prompt
“Review the product backlog. Flag tickets older than 90 days, identify duplicates, and highlight stories missing acceptance criteria.”
Set Up Jira MCP in Minutes
Add the following configuration to your MCP client. Authentication is handled via OAuth through Willow's SSO integration.
Claude Desktop / Cursor
{
"mcpServers": {
"willow-jira": {
"type": "http",
"url": "https://<org>.mcp-s.com/mcp/mcp/jira"
}
}
}Claude Code CLI
claude mcp add willow-jira --transport http https://<org>.mcp-s.com/mcp/mcp/jira
Enterprise Governance Included
Project-Level RBAC
Control which Jira projects AI agents can access. Engineering agents read the Engineering project — they never touch HR or Finance projects.
SSO Authentication
Agents authenticate through your SSO. No Jira API tokens distributed to individuals or stored in configurations.
Action Audit Logging
Every Jira issue created, updated, or read by an AI agent is logged — with the agent identity, timestamp, and full action details.
Write Permission Granularity
Configure agents with read-only access for reporting, or write access limited to specific projects and issue types — never broad admin permissions.
Frequently Asked Questions
Can AI agents create and update Jira issues, or just read them?
Both. Willow's Jira MCP supports creating issues, updating fields, adding comments, transitioning workflow states, and linking issues. Write permissions are governed by RBAC — configure which operations agents can perform per project.
Does this work with Jira Software and Jira Service Management?
Yes. Willow's Jira MCP works with Jira Software (for engineering sprints) and Jira Service Management (for IT/support). Configure access per project type.
Can AI agents estimate story points?
Yes. AI agents can analyze issue descriptions, acceptance criteria, and historical team velocity to suggest story point estimates. Estimates are suggestions — engineers review and confirm before sprint commitment.
How does this integrate with GitHub or other dev tools?
Combine Willow's Jira MCP with the GitHub MCP server for end-to-end engineering workflows — create Jira tickets from GitHub issues, link PRs to stories, and generate release notes from merged PRs and closed tickets.
Automate Your Engineering Workflows with Jira MCP
Install the Jira MCP server and run your first AI-powered sprint report.