atlassian-mcp

jeffallan/claude-skills · updated May 28, 2026

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$npx skills add https://github.com/jeffallan/claude-skills --skill atlassian-mcp
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summary

Jira and Confluence automation via MCP protocol with JQL/CQL queries, ticket management, and sprint workflows.

  • Supports querying Jira issues with JQL filters, creating and updating tickets with custom fields, and managing sprints and backlogs
  • Enables searching, creating, and editing Confluence pages using CQL syntax with space and content management
  • Includes authentication patterns for OAuth 2.0, API tokens, and PAT credentials with permission scope validation
  • Provides reference g
skill.md

Atlassian MCP Expert

When to Use This Skill

  • Querying Jira issues with JQL filters
  • Searching or creating Confluence pages
  • Automating sprint workflows and backlog management
  • Setting up MCP server authentication (OAuth/API tokens)
  • Syncing meeting notes to Jira tickets
  • Generating documentation from issue data
  • Debugging Atlassian API integration issues
  • Choosing between official vs open-source MCP servers

Core Workflow

  1. Select server - Choose official cloud, open-source, or self-hosted MCP server
  2. Authenticate - Configure OAuth 2.1, API tokens, or PAT credentials
  3. Design queries - Write JQL for Jira, CQL for Confluence; validate with maxResults=1 before full execution
  4. Implement workflow - Build tool calls, handle pagination, error recovery
  5. Verify permissions - Confirm required scopes with a read-only probe before any write or bulk operation
  6. Deploy - Configure IDE integration, test permissions, monitor rate limits

Reference Guide

Load detailed guidance based on context:

Topic Reference Load When
Server Setup references/mcp-server-setup.md Installation, choosing servers, configuration
Jira Operations references/jira-queries.md JQL syntax, issue CRUD, sprints, boards, issue linking
Confluence Ops references/confluence-operations.md CQL search, page creation, spaces, comments
Authentication references/authentication-patterns.md OAuth 2.0, API tokens, permission scopes
Common Workflows references/common-workflows.md Issue triage, doc sync, sprint automation

Quick-Start Examples

JQL Query Samples

# Open issues assigned to current user in a sprint
project = PROJ AND status = "In Progress" AND assignee = currentUser() ORDER BY priority DESC

# Unresolved bugs created in the last 7 days
project = PROJ AND issuetype = Bug AND status != Done AND created >= -7d ORDER BY created DESC

# Validate before bulk: test with maxResults=1 first
project = PROJ AND sprint in openSprints() AND status = Open ORDER BY created DESC

CQL Query Samples

# Find pages updated in a specific space recently
space = "ENG" AND type = page AND lastModified >= "2024-01-01" ORDER BY lastModified DESC

# Search page text for a keyword
space = "ENG" AND type = page AND text ~ "deployment runbook"

Minimal MCP Server Configuration

{
  "mcpServers": {
    "atlassian": {
      "command": "npx",
      "args": ["-y", "@sooperset/mcp-atlassian"],
      "env": {
        "JIRA_URL": "https://your-domain.atlassian.net",
        "JIRA_EMAIL": "[email protected]",
        "JIRA_API_TOKEN": "${JIRA_API_TOKEN}",
        "CONFLUENCE_URL": "https://your-domain.atlassian.net/wiki",
        "CONFLUENCE_EMAIL": "[email protected]",
        "CONFLUENCE_API_TOKEN": "${CONFLUENCE_API_TOKEN}"
      }
    }
  }
}

Note: Always load JIRA_API_TOKEN and CONFLUENCE_API_TOKEN from environment variables or a secrets manager — never hardcode credentials.

Constraints

MUST DO

  • Respect user permissions and workspace access controls
  • Validate JQL/CQL queries before execution (use maxResults=1 probe first)
  • Handle rate limits with exponential backoff
  • Use pagination for large result sets (50-100 items per page)
  • Implement error recovery for network failures
  • Log API calls for debugging and audit trails
  • Test with read-only operations first
  • Document required permission scopes
  • Confirm before any write or bulk operation against production data

MUST NOT DO

  • Hardcode API tokens or OAuth secrets in code
  • Ignore rate limit headers from Atlassian APIs
  • Create issues without validating required fields
  • Skip input sanitization on user-provided query strings
  • Deploy without testing permission boundaries
  • Update production data without confirmation prompts
  • Mix different authentication methods in same session
  • Expose sensitive issue data in logs or error messages

Output Templates

When implementing Atlassian MCP features, provide:

  1. MCP server configuration (JSON/environment vars)
  2. Query examples (JQL/CQL with explanations)
  3. Tool call implementation with error handling
  4. Authentication setup instructions
  5. Brief explanation of permission requirements
how to use atlassian-mcp

How to use atlassian-mcp on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add atlassian-mcp
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jeffallan/claude-skills --skill atlassian-mcp

The skills CLI fetches atlassian-mcp from GitHub repository jeffallan/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/atlassian-mcp

Reload or restart Cursor to activate atlassian-mcp. Access the skill through slash commands (e.g., /atlassian-mcp) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.674 reviews
  • Kabir Gill· Dec 28, 2024

    Solid pick for teams standardizing on skills: atlassian-mcp is focused, and the summary matches what you get after install.

  • Emma Anderson· Dec 28, 2024

    Useful defaults in atlassian-mcp — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Pratham Ware· Dec 24, 2024

    atlassian-mcp reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Yusuf Jackson· Dec 24, 2024

    Registry listing for atlassian-mcp matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Chaitanya Patil· Dec 16, 2024

    Solid pick for teams standardizing on skills: atlassian-mcp is focused, and the summary matches what you get after install.

  • Kofi Sanchez· Dec 12, 2024

    Registry listing for atlassian-mcp matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Yuki Ghosh· Dec 8, 2024

    atlassian-mcp reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Luis Diallo· Dec 8, 2024

    We added atlassian-mcp from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Michael Kim· Dec 4, 2024

    atlassian-mcp fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yusuf Robinson· Nov 27, 2024

    Solid pick for teams standardizing on skills: atlassian-mcp is focused, and the summary matches what you get after install.

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