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Atlassian MCP (Jira, Confluence)

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Run the Model Context Protocol (MCP) Atlassian server in Docker, enabling integration with Jira, Confluence, and other Atlassian products. Use when you need to query Jira issues, search Confluence, or interact with Atlassian services programmatically. Requires Docker and valid Jira API credentials.

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About This Skill

# MCP Atlassian

Overview

The MCP Atlassian server provides programmatic access to Jira and other Atlassian services through the Model Context Protocol. Run it in Docker with your Jira credentials to query issues, manage projects, and interact with Atlassian tools.

Quick Start

Pull and run the container with your Jira credentials:

```bash docker pull ghcr.io/sooperset/mcp-atlassian:latest

docker run --rm -i \ -e JIRA_URL=https://your-company.atlassian.net \ -e [email protected] \ -e JIRA_API_TOKEN=your_api_token \ ghcr.io/sooperset/mcp-atlassian:latest ```

With script (faster):

Run the bundled script with your API token:

```bash JIRA_API_TOKEN=your_token bash scripts/run_mcp_atlassian.sh ```

Environment Variables

  • JIRA_URL: Your Atlassian instance URL (e.g., `https://company.atlassian.net`)
  • JIRA_USERNAME: Your Jira email address
  • JIRA_API_TOKEN: Your Jira API token (create in Account Settings → Security)

Using MCP Atlassian with Clawdbot

Once running, the MCP server exposes Jira tools for use. Reference the container as an MCP source in your Clawdbot config to query issues, create tasks, or manage Jira directly from your agent.

Resources

scripts/ - **run_mcp_atlassian.sh** - Simplified runner script with credential handling

Use Cases

  • Query and filter Jira issues from an AI agent to automate sprint triage
  • Create and update Jira tickets programmatically during development workflows
  • Search Confluence documentation from within an agent session for context gathering
  • Build automated standup reports by pulling recent Jira activity via MCP
  • Integrate Atlassian project data into AI-powered code review or planning pipelines

Pros & Cons

Pros

  • + Runs in Docker with a single command — no local dependency installation needed
  • + Standard MCP protocol makes it composable with any MCP-compatible AI agent
  • + Includes a bundled helper script for simplified credential management and startup

Cons

  • - Requires Docker to be installed and running on the host machine
  • - Needs a Jira API token with appropriate permissions — not all organizations allow this
  • - Limited to Jira and Confluence — does not cover Bitbucket, Trello, or other Atlassian products

Frequently Asked Questions

What does Atlassian MCP (Jira, Confluence) do?

Run the Model Context Protocol (MCP) Atlassian server in Docker, enabling integration with Jira, Confluence, and other Atlassian products. Use when you need to query Jira issues, search Confluence, or interact with Atlassian services programmatically. Requires Docker and valid Jira API credentials.

What platforms support Atlassian MCP (Jira, Confluence)?

Atlassian MCP (Jira, Confluence) is available on Claude Code, OpenClaw.

What are the use cases for Atlassian MCP (Jira, Confluence)?

Query and filter Jira issues from an AI agent to automate sprint triage. Create and update Jira tickets programmatically during development workflows. Search Confluence documentation from within an agent session for context gathering.

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