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phuc-nt/mcp-atlassian-server: MCP server connecting AI assistants with Jira & Confluence for smart project management.

• Refactored the entire codebase to standardize resource/tool structure, completely removed the content-metadata resource, and merged metadata into the page resource.
• New developer guide: anyone can now easily extend and maintain the codebase.
• Ensured compatibility with the latest MCP SDK, improved security, scalability, and maintainability.
• Updated docs/introduction/resources-and-tools.md to remove all references to content-metadata.

👉 See the full CHANGELOG for details.

MCP Atlassian Server v2.0.1 brings a major expansion of features and capabilities!

• Updated APIs: Now using the latest Atlassian APIs (Jira API v3, Confluence API v2)
• Expanded Features: Grown from 21 to 48 features, including advanced Jira and Confluence capabilities
• Enhanced Board & Sprint Management: Complete Agile/Scrum workflow support
• Advanced Confluence Features: Page version management, attachments handling, and comment management
• Improved Resource Registration: Fixed duplicate resource registration issues for a more stable experience
• Documentation Update: New comprehensive documentation series explaining MCP architecture, resource/tool development

For full details on all changes, improvements, and fixes, see the CHANGELOG.

MCP Atlassian Server (by phuc-nt) is a Model Context Protocol (MCP) server that connects AI agents like Cline, Claude Desktop, or Cursor to Atlassian Jira and Confluence, enabling them to query data and perform actions through a standardized interface.

Note: This server is primarily designed and optimized for use with Cline, though it follows the MCP standard and can work with other MCP-compatible clients.

• Key Features:
  • Connect AI agents to Atlassian Jira and Confluence
  • Support both Resources (read-only) and Tools (actions/mutations)
  • Easy integration with Cline through MCP Marketplace
  • Local-first design for personal development environments
  • Optimized integration with Cline AI assistant

As a developer working daily with Jira and Confluence, I found myself spending significant time navigating these tools. While they're powerful, I longed for a simpler way to interact with them without constantly context-switching during deep work.

The emergence of AI Agents and the Model Context Protocol (MCP) presented the perfect opportunity. I immediately saw the potential to connect Jira and Confluence (with plans for Slack, GitHub, Calendar, and more) to my AI workflows.

This project began as a learning journey into MCP and AI Agents, but I hope it evolves into something truly useful for individuals and organizations who interact with Atlassian tools daily.

graph TD
    AI[Cline AI Assistant] <--> MCP[MCP Atlassian Server]
    MCP <--> JiraAPI[Jira API]
    MCP <--> ConfAPI[Confluence API]
    
    subgraph "MCP Server"
        Resources[Resources - Read Only] 
        Tools[Tools - Actions]
    end
    
    Resources --> JiraRes[Jira Resources<br/>issues, projects, users]
    Resources --> ConfRes[Confluence Resources<br/>spaces, pages]
    Tools --> JiraTools[Jira Tools<br/>create, update, transition]
    Tools --> ConfTools[Confluence Tools<br/>create page, comment]

For detailed installation and setup instructions, please refer to our installation guide for AI assistants. This guide is specially formatted for AI/LLM assistants like Cline to read and automatically set up the MCP Atlassian Server.

Note for Cline users: The installation guide (llms-install.md) is optimized for Cline AI to understand and execute. You can simply ask Cline to "Install MCP Atlassian Server (by phuc-nt)" and it will be able to parse the instructions and help you set up everything step-by-step.

The guide includes:

• Prerequisites and system requirements
• Step-by-step setup for Node.js environments
• Configuring Cline AI assistant to connect with Atlassian
• Getting and setting up Atlassian API tokens
• Security recommendations and best practices

To install Atlassian Integration Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @phuc-nt/mcp-atlassian-server --client claude

MCP Atlassian Server enables AI assistants (like Cline, Claude Desktop, Cursor...) to access and manage Jira & Confluence with a full set of features, grouped for clarity:

• Issue Management

  • View, search, and filter issues
  • Create, update, transition, and assign issues
  • Add issues to backlog or sprint, rank issues

• Project Management

  • View project list, project details, and project roles

• Board & Sprint Management

  • View boards, board configuration, issues and sprints on boards
  • Create, start, and close sprints

• Filter Management

  • View, create, update, and delete filters

• Dashboard & Gadget Management

  • View dashboards and gadgets
  • Create and update dashboards
  • Add or remove gadgets on dashboards

• User Management

  • View user details, assignable users, and users by project role

• Space Management

  • View space list, space details, and pages in a space

• Page Management

  • View, search, and get details of pages, child pages, ancestors, attachments, and version history
  • Create, update, rename, and delete pages

• Comment Management

  • View, add, update, and delete comments on pages

For a full technical breakdown of all features, resources, and tools, see: docs/introduction/resources-and-tools.md

sequenceDiagram
    participant User
    participant Cline as Cline AI
    participant MCP as MCP Server
    participant Atlassian as Atlassian API
    
    User->>Cline: "Find all my assigned issues"
    Cline->>MCP: Request jira://issues
    MCP->>Atlassian: API Request with Auth
    Atlassian->>MCP: JSON Response
    MCP->>Cline: Formatted MCP Resource
    Cline->>User: "I found these issues..."
    
    User->>Cline: "Create new issue about login bug"
    Cline->>MCP: Call createIssue Tool
    MCP->>Atlassian: POST /rest/api/3/issue
    Atlassian->>MCP: Created Issue Data
    MCP->>Cline: Success Response
    Cline->>User: "Created issue DEMO-123"

• Your API token inherits all permissions of the user that created it
• Never share your token with a non-trusted party
• Be cautious when asking LLMs to analyze config files containing your token
• See detailed security guidelines in llms-install.md

• Contribute by opening Pull Requests or Issues on GitHub.
• Join the MCP/Cline community for additional support.

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