Jira MCP Server

How to use

You’ll use an MCP client to interact with the Jira MCP Server. Start by configuring one or more Jira instances in your working environment, then connect through an MCP client to perform actions such as creating and updating issues, querying with JQL, managing sprints and epics, and running bulk operations. The server handles session isolation, per-session configuration caching, and automatic session timeouts, so each client session remains independent and high-concurrency friendly.

How to install

# Prerequisites
- Node.js installed (version supported by the MCP server)
- npm installed
- Access to Jira with API tokens
```

```
# 1) Installing via npm (global CLI)
npm install -g jira-server
```

```
# 2) Installing via Smithery (Claude Desktop integration)
npx -y @smithery/cli install jira-server --client claude
```

```
# 3) Manual installation (clone, install, build)
# Clone the project, then:
npm install
npm run build
```

```
# Start the server (if manually started from built index)
node build/index.js

Configuration and usage notes

Configuration supports multiple Jira instances from a single Claude Desktop session. Create a configuration file that maps projects to instances and defines field IDs for Story Points, Sprint, and Epic Link. You can also enable automatic field detection to discover custom fields on first access.

Security and access

Use API tokens and per-user credentials for Jira access. Each client session maintains isolated state, reducing cross-session interference. Ensure you configure appropriate permissions and token scopes in Jira to allow the actions your workflows require.

Troubleshooting tips

If you encounter issues, check session logs and debug output for field discovery messages or authentication errors. Use multi-instance validation commands to verify correct mappings and ensure Jira projects are accessible with the configured tokens.

Notes on cross-server and analytics features

You can enable cross-server health checks and cross-server integration with companion MCP servers where supported. The server includes analytic capabilities such as progress tracking, trend insights, and workload distribution to support strategic planning and project governance.

Usage examples overview

Practical workflows include creating issues with automatic field handling, updating time estimates, querying with JQL for cross-project insights, creating components and versions for release planning, and performing bulk updates across multiple issues or sprints.

create_issue

Create new Jira issues with comprehensive field support including auto-detection of story points and sprint assignment

list_issues

List and filter issues with status, epic_key, and projectKey parameters and display sprint info and ranking

update_issue

Update issues with full field support including time tracking, epic linking, and intelligent assignee resolution

get_issue

Retrieve detailed issue data including comments and relationships

delete_issue

Safely remove issues from projects

add_comment

Add comments to existing issues

get_transitions

Get available workflow transitions for an issue to plan changes before applying them

transition_issue

Apply a workflow transition to an issue with optional comment and resolution

list_custom_fields

Discover available custom fields and obtain ready-to-copy configuration snippets

list_instances

List configured Jira instances, project mappings, and validation guidance

create_component

Create project components to organize work by feature areas

list_components

List all project components with details and ownership information

get_component_progress

Provide analytics on component progress, status, recent activity, and workload

create_version

Create project versions for release planning and milestone tracking

list_versions

List project versions with status and timeline information

get_version_progress

Analyze version progress with completion and deadline insights

search_issues_jql

Execute advanced JQL queries with pagination and result analytics

search_projects

Discover projects across the Jira organization with filtering

create_filter

Create and share saved filters for consistent tracking

get_project_details

Fetch comprehensive project metadata and structure

get_project_statuses

Analyze workflow statuses and transition mappings

get_issue_types

Discover issue type configurations and requirements

detect_project_fields

Automatically detect custom field IDs for project configuration and provide ready snippets

jira_health_check

Monitor Jira server health and cross-server integration status

confluence_health_check

Monitor Confluence integration health as part of cross-server setup

list_plans

Manage high-level strategic plans and roadmaps (Jira Premium)

create_sprint

Create sprints with goals and timelines

update_sprint

Modify sprint details and timelines

get_sprint_details

Analyze sprint progress with velocity and burndown data

move_issues_to_sprint

Bulk assign issues to a sprint

complete_sprint

Close active sprints and handle remaining work

create_epic

Create epics for large feature organization

create_epic_with_issues

Create an epic with linked issues in a single operation

update_epic_details

Update epic properties and status

rank_epics

Rank epics by priority

rank_issues

Rank issues within a project

bulk_update_issues

Bulk update multiple issues with status, assignee, and attributes

list_boards

List Kanban and Scrum boards in the Jira instance

get_board_configuration

Analyze board setup and column configuration

get_sprint_report

Get sprint performance metrics like velocity and burndown

get_velocity_chart_data

Extract velocity chart data for team performance

get_burndown_chart_data

Extract burndown chart data for sprint progress

detect_project_fields

Field discovery and configuration guidance