MCP Atlassian
Model Context Protocol server for integrating with Atlassian products (Confluence and Jira) that supports both Atlassian Cloud and Server/Data Center deployments.
adamjbird2
README
MCP Atlassian
Model Context Protocol (MCP) server for Atlassian products (Confluence and Jira). This integration supports both Atlassian Cloud and Server/Data Center deployments.
Feature Demo
<details> <summary>Confluence Demo</summary>
</details>
Compatibility
Product | Deployment Type | Support Status |
---|---|---|
Confluence | Cloud | ✅ Fully supported |
Confluence | Server/Data Center | ✅ Supported (version 7.9+) |
Jira | Cloud | ✅ Fully supported |
Jira | Server/Data Center | ✅ Supported (version 8.14+) |
Setup Guide
1. Authentication Setup
First, generate the necessary authentication tokens:
For Atlassian Cloud
- Go to https://id.atlassian.com/manage-profile/security/api-tokens
- Click Create API token, name it
- Copy the token immediately
For Server/Data Center
- Go to your profile (avatar) → Profile → Personal Access Tokens
- Click Create token, name it, set expiry
- Copy the token immediately
2. Installation
Choose one of these installation methods:
# Using uv (recommended)
brew install uv
uvx mcp-atlassian
# Using pip
pip install mcp-atlassian
# Using Docker
git clone https://github.com/sooperset/mcp-atlassian.git
cd mcp-atlassian
docker build -t mcp/atlassian .
3. Configuration and Usage
You can configure the MCP server using command line arguments. The server supports using either Confluence, Jira, or both services - include only the arguments needed for your use case.
Required Arguments
For Atlassian Cloud:
uvx mcp-atlassian \
--confluence-url https://your-company.atlassian.net/wiki \
--confluence-username your.email@company.com \
--confluence-token your_api_token \
--jira-url https://your-company.atlassian.net \
--jira-username your.email@company.com \
--jira-token your_api_token
For Server/Data Center:
uvx mcp-atlassian \
--confluence-url https://confluence.your-company.com \
--confluence-personal-token your_token \
--jira-url https://jira.your-company.com \
--jira-personal-token your_token
Note: You can configure just Confluence, just Jira, or both services. Simply include only the arguments for the service(s) you want to use. For example, to use only Confluence Cloud, you would only need
--confluence-url
,--confluence-username
, and--confluence-token
.
Optional Arguments
--transport
: Choose transport type (stdio
[default] orsse
)--port
: Port number for SSE transport (default: 8000)--[no-]confluence-ssl-verify
: Toggle SSL verification for Confluence Server/DC--[no-]jira-ssl-verify
: Toggle SSL verification for Jira Server/DC--verbose
: Increase logging verbosity (can be used multiple times)--read-only
: Run in read-only mode (disables all write operations)
Note: All configuration options can also be set via environment variables. See the
.env.example
file in the repository for the full list of available environment variables.
IDE Integration
Claude Desktop Setup
Using uvx (recommended) - Cloud:
{
"mcpServers": {
"mcp-atlassian": {
"command": "uvx",
"args": [
"mcp-atlassian",
"--confluence-url=https://your-company.atlassian.net/wiki",
"--confluence-username=your.email@company.com",
"--confluence-token=your_api_token",
"--jira-url=https://your-company.atlassian.net",
"--jira-username=your.email@company.com",
"--jira-token=your_api_token"
]
}
}
}
<details> <summary>Using uvx (recommended) - Server/Data Center </summary>
{
"mcpServers": {
"mcp-atlassian": {
"command": "uvx",
"args": [
"mcp-atlassian",
"--confluence-url=https://confluence.your-company.com",
"--confluence-personal-token=your_token",
"--jira-url=https://jira.your-company.com",
"--jira-personal-token=your_token"
]
}
}
}
</details>
<details> <summary>Using pip</summary>
Note: Examples below use Atlassian Cloud configuration. For Server/Data Center, use the corresponding arguments (--confluence-personal-token, --jira-personal-token) as shown in the Configuration section above.
{
"mcpServers": {
"mcp-atlassian": {
"command": "python",
"args": [
"-m",
"mcp-atlassian",
"--confluence-url=https://your-company.atlassian.net/wiki",
"--confluence-username=your.email@company.com",
"--confluence-token=your_api_token",
"--jira-url=https://your-company.atlassian.net",
"--jira-username=your.email@company.com",
"--jira-token=your_api_token"
]
}
}
}
</details>
<details> <summary>Using docker</summary>
Note: Examples below use Atlassian Cloud configuration. For Server/Data Center, use the corresponding arguments (--confluence-personal-token, --jira-personal-token) as shown in the Configuration section above.
There are two ways to configure the Docker environment:
- Using cli arguments directly in the config:
{
"mcpServers": {
"mcp-atlassian": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"mcp/atlassian",
"--confluence-url=https://your-company.atlassian.net/wiki",
"--confluence-username=your.email@company.com",
"--confluence-token=your_api_token",
"--jira-url=https://your-company.atlassian.net",
"--jira-username=your.email@company.com",
"--jira-token=your_api_token"
]
}
}
}
- Using an environment file:
{
"mcpServers": {
"mcp-atlassian": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"--env-file",
"/path/to/your/.env",
"mcp/atlassian"
]
}
}
}
</details>
Cursor IDE Setup
- Open Cursor Settings
- Navigate to
Features
>MCP Servers
- Click
Add new MCP server
For stdio transport:
name: mcp-atlassian
type: command
command: uvx mcp-atlassian --confluence-url=https://your-company.atlassian.net/wiki --confluence-username=your.email@company.com --confluence-token=your_api_token --jira-url=https://your-company.atlassian.net --jira-username=your.email@company.com --jira-token=your_api_token
<details> <summary>Server/Data Center Configuration</summary>
name: mcp-atlassian
type: command
command: uvx mcp-atlassian --confluence-url=https://confluence.your-company.com --confluence-personal-token=your_token --jira-url=https://jira.your-company.com --jira-personal-token=your_token
</details>
For SSE transport, first start the server:
uvx mcp-atlassian ... --transport sse --port 8000
Then configure in Cursor:
name: mcp-atlassian
type: sse
Server URL: http://localhost:8000/sse
Resources
Note: The MCP server filters resources to only show Confluence spaces and Jira projects that the user is actively interacting with, based on their contributions and assignments.
confluence://{space_key}
: Access Confluence spacesjira://{project_key}
: Access Jira projects
Available Tools
Tool | Description |
---|---|
confluence_search |
Search Confluence content using CQL |
confluence_get_page |
Get content of a specific Confluence page |
confluence_get_page_children |
Get child pages of a specific Confluence page |
confluence_get_page_ancestors |
Get parent pages of a specific Confluence page |
confluence_get_comments |
Get comments for a specific Confluence page |
confluence_create_page |
Create a new Confluence page |
confluence_update_page |
Update an existing Confluence page |
confluence_delete_page |
Delete an existing Confluence page |
jira_get_issue |
Get details of a specific Jira issue |
jira_search |
Search Jira issues using JQL |
jira_get_project_issues |
Get all issues for a specific Jira project |
jira_create_issue |
Create a new issue in Jira |
jira_update_issue |
Update an existing Jira issue |
jira_delete_issue |
Delete an existing Jira issue |
jira_get_transitions |
Get available status transitions for a Jira issue |
jira_transition_issue |
Transition a Jira issue to a new status |
jira_add_worklog |
Add a worklog entry to a Jira issue |
jira_get_worklog |
Get worklog entries for a Jira issue |
jira_link_to_epic |
Link an issue to an Epic |
jira_get_epic_issues |
Get all issues linked to a specific Epic |
Development & Debugging
Local Development Setup
If you've cloned the repository and want to run a local version:
{
"mcpServers": {
"mcp-atlassian": {
"command": "uv",
"args": [
"--directory", "/path/to/your/mcp-atlassian",
"run", "mcp-atlassian",
"--confluence-url=https://your-domain.atlassian.net/wiki",
"--confluence-username=your.email@domain.com",
"--confluence-token=your_api_token",
"--jira-url=https://your-domain.atlassian.net",
"--jira-username=your.email@domain.com",
"--jira-token=your_api_token"
]
}
}
}
Debugging Tools
# Using MCP Inspector
# For installed package
npx @modelcontextprotocol/inspector uvx mcp-atlassian ...
# For local development version
npx @modelcontextprotocol/inspector uv --directory /path/to/your/mcp-atlassian run mcp-atlassian ...
# View logs
tail -n 20 -f ~/Library/Logs/Claude/mcp*.log
Security
- Never share API tokens
- Keep .env files secure and private
- See SECURITY.md for best practices
License
Licensed under MIT - see LICENSE file. This is not an official Atlassian product.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
MCP Package Docs Server
Facilitates LLMs to efficiently access and fetch structured documentation for packages in Go, Python, and NPM, enhancing software development with multi-language support and performance optimization.
Claude Code MCP
An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.
@kazuph/mcp-taskmanager
Model Context Protocol server for Task Management. This allows Claude Desktop (or any MCP client) to manage and execute tasks in a queue-based system.
Linear MCP Server
Enables interaction with Linear's API for managing issues, teams, and projects programmatically through the Model Context Protocol.
mermaid-mcp-server
A Model Context Protocol (MCP) server that converts Mermaid diagrams to PNG images.
Jira-Context-MCP
MCP server to provide Jira Tickets information to AI coding agents like Cursor

Linear MCP Server
A Model Context Protocol server that integrates with Linear's issue tracking system, allowing LLMs to create, update, search, and comment on Linear issues through natural language interactions.

Sequential Thinking MCP Server
This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.