Atlassian Mcp logo

Atlassian Mcp

CommunityPopular
Jeffallan
atlassian-mcp

Integrates with Atlassian products to manage project tracking and documentation via MCP protocol. Use when querying Jira issues with JQL filters, creating and updating tickets with custom fields, searching or editing Confluence pages with CQL, managing sprints and backlogs, setting up MCP server authentication, syncing documentation, or debugging Atlassian API integrations.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill nameatlassian-mcp
Stars
11.5K
Forks
1.1K
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Jeffallan on GitHub. Read the source before you install it.

Installation

Install the Atlassian Mcp AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/atlassian-mcp .claude/skills/atlassian-mcp
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Atlassian Mcp in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Atlassian Mcp on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Atlassian Mcp is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

TopicReferenceLoad When
Server Setupreferences/mcp-server-setup.mdInstallation, choosing servers, configuration
Jira Operationsreferences/jira-queries.mdJQL syntax, issue CRUD, sprints, boards, issue linking
Confluence Opsreferences/confluence-operations.mdCQL search, page creation, spaces, comments
Authenticationreferences/authentication-patterns.mdOAuth 2.0, API tokens, permission scopes
Common Workflowsreferences/common-workflows.mdIssue 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

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

Documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Atlassian Mcp AI skill do?

Integrates with Atlassian products to manage project tracking and documentation via MCP protocol. Use when querying Jira issues with JQL filters, creating and updating tickets with custom fields, searching or editing Confluence pages with CQL, managing sprints and backlogs, setting up MCP server authentication, syncing documentation, or debugging Atlassian API integrations.

Why use Atlassian Mcp on TypingMind?

Because you install it once and use it with any model. Atlassian Mcp is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Atlassian Mcp in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/atlassian-mcp. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Atlassian Mcp?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Atlassian Mcp?

As many as you like. As long as a model supports skills, you can use Atlassian Mcp with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Atlassian Mcp AI skill free?

Yes. It is published on GitHub by Jeffallan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇