Jira MCP Server
Provides tools to interact with Jira API, enabling creation, deletion, updating, and querying of issues, boards, epics, and projects.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Jira MCP ServerList all Jira projects"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Jira MCP Server
This is a Model Context Protocol (MCP) server that exposes Jira API calls as tools for use with Claude and other AI models.
Setup
1. Install Dependencies
pip install -r requirements.txt2. Configure Environment Variables
Create a .env file in the project root:
JIRA_EMAIL=your.email@gmail.com
JIRA_API_TOKEN=your_api_token_here
JIRA_BASE_URL=https://your-instance.atlassian.netNote: Get your API token from: https://id.atlassian.com/manage-profile/security/api-tokens
3. Run the Client
python test_client.pyRelated MCP server: Jira MCP Integration
Available Tools
The MCP server exposes the following tools:
1. list_projects
List all Jira projects
No parameters required
2. get_boards
Get all Agile boards
No parameters required
3. get_board_columns
Get columns for a specific board
board_id(integer): The ID of the board
4. get_issues_for_board
Get all issues for a specific board
board_id(integer): The ID of the board
5. get_epics_from_board
Get all epics from a specific board
board_id(integer): The ID of the board
6. create_issue
Create a new issue in Jira
project_key(string): Project key (e.g., 'KAN')summary(string): Issue summary/titledescription(string): Issue descriptionissue_type(string, optional): Issue type (Task, Epic, Story, etc.) - defaults to "Task"
7. delete_issue
Delete an issue from Jira
issue_key(string): Issue key (e.g., 'KAN-4')
8. update_issue_status
Update the status of an issue
issue_key(string): Issue key (e.g., 'KAN-1')transition_id(string): Transition ID for the new status
Usage with Claude
To use this MCP server with Claude, add it to your Claude config:
macOS/Linux: ~/.config/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"jira": {
"command": "python",
"args": ["/path/to/mcp_server.py"],
"env": {
"JIRA_EMAIL": "your.email@gmail.com",
"JIRA_API_TOKEN": "your_api_token",
"JIRA_BASE_URL": "https://your-instance.atlassian.net"
}
}
}
}Project Structure
.
├── test_client.py # Client to run the server tools calls test
├── mcp_server.py # Main MCP server implementation
├── api_calls/ # Original API call scripts (reference)
│ ├── create_issue_from_json.py
│ ├── delete_issue.py
│ ├── get_board_columns.py
│ ├── get_boards.py
│ ├── get_epics_from_board.py
│ ├── get_issues_for_board.py
│ ├── list_projects.py
│ └── update_issue_status.py
├── package.json # Project metadata
├── requirements.txt # Python dependencies
└── README.md # This fileKey Improvements Over Individual Scripts
✅ Unified Interface: All API calls accessible via a single MCP server
✅ Security: Credentials managed via environment variables
✅ Error Handling: Consistent error handling across all tools
✅ Type Safety: Proper input schema validation
✅ Extensibility: Easy to add new tools
✅ Integration: Seamless integration with Claude and other AI models
This server cannot be deployed
Maintenance
Related MCP Connectors
Connect to Atlassian Jira, Confluence, Loom, and more to search, create, and manage your work.
Task management for people and AI agents, with scoped OAuth access to issues, projects, and docs.
AI-callable tools for API mocking, testing, monitoring, security, and automation.
- KaneraOAuthapp.kanera
Manage Kanera workspaces, boards, cards, checklists, comments, notes, automations, and reports.
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