Provides Jira issue, sprint, transition, and development data access through MCP-enabled workflows.
Configuration
View docs{
"mcpServers": {
"jira": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"ATLASSIAN_HOST=https://your-company.atlassian.net",
"-e",
"[email protected]",
"-e",
"ATLASSIAN_TOKEN=your-api-token",
"ghcr.io/nguyenvanduocit/jira-mcp:latest"
],
"env": {
"ATLASSIAN_HOST": "https://your-company.atlassian.net",
"ATLASSIAN_EMAIL": "[email protected]",
"ATLASSIAN_TOKEN": "your-api-token"
}
}
}
}You run a Jira MCP Server that connects your Jira workflows to an AI assistant, enabling practical automation like retrieving issue details, managing sprints, linking work across development tools, and capturing development information in one place. This server is built around real-world Jira usage patterns, giving you actionable tools to streamline development, sprint planning, and release visibility.
You interact with Jira MCP through an MCP client or Cursor-like interface. Use commands and prompts that reflect common Jira workflows, such as asking for an issue’s status, listing active or future sprints, creating and updating issues, adding comments or worklogs, and retrieving development information linked to an issue. The server exposes a focused set of tools designed to help you manage issues, sprints, transitions, comments, worklogs, history, relationships, versions, and development data from connected repositories.
Prerequisites: you need either Docker or a local binary to run the Jira MCP server. You also need a Jira API token for authentication.
Step 1. Get an API token. Create one at the Atlassian API token page.
Step 2. Choose a.run method and prepare your MCP configuration.
Step 3. Start the Jira MCP server using one of the provided configurations.
You configure the server by providing environment variables and runtime commands. The examples below show two explicit ways to run the Jira MCP server: via Docker or as a local binary. In both cases you supply your Jira host, account email, and API token.
{
"mcpServers": {
"jira": {
"command": "docker",
"args": [
"run", "--rm", "-i",
"-e", "ATLASSIAN_HOST=https://your-company.atlassian.net",
"-e", "[email protected]",
"-e", "ATLASSIAN_TOKEN=your-api-token",
"ghcr.io/nguyenvanduocit/jira-mcp:latest"
]
}
}
}{
"mcpServers": {
"jira": {
"command": "/usr/local/bin/jira-mcp",
"env": {
"ATLASSIAN_HOST": "https://your-company.atlassian.net",
"ATLASSIAN_EMAIL": "[email protected]",
"ATLASSIAN_TOKEN": "your-api-token"
}
}
}
}Retrieve detailed information about a specific issue including status, assignee, description, subtasks, and available transitions
Create a new issue with specified details (returns key, ID, and URL)
Create a child issue (sub-task) linked to a parent issue
Modify an existing issue's details (supports partial updates)
List all available issue types in a project with their IDs, names, and descriptions
Search for issues using JQL with customizable fields and expand options
List all active and future sprints for a specific board or project
Retrieve detailed information about a specific sprint by its ID
Get the currently active sprint for a given board or project
Search for sprints by name with exact or partial matching
Retrieve all available issue status IDs and their names for a project
Transition an issue through its workflow using a valid transition ID
Add a comment to an issue (uses Atlassian Document Format)
Retrieve all comments from an issue
Add a worklog entry to track time spent on an issue
Retrieve the complete change history of an issue
Retrieve issues that have a relationship (blocks, is blocked by, relates to, etc.)
Create a link between two issues, defining their relationship
Retrieve detailed information about a specific project version
List all versions in a project with their details
Retrieve branches, pull requests, and commits linked to an issue via development tool integrations