MCP Servers · sooperset

mcp-atlassian

mcp-atlassian is a Python-based MCP (Model Context Protocol) server that enables AI assistants like Claude to interact directly with Atlassian tools—Jira and Confluence—across Cloud and Server/Data Center deployments. It provides 80+ tools for searching issues, creating tickets, reading documentation, and managing workflows programmatically.

Talk to DEV.co Discuss Implementation

Source: GitHub — github.com/sooperset/mcp-atlassian

5.5k

GitHub stars

1.3k

Forks

Python

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	sooperset/mcp-atlassian
Owner	sooperset
Primary language	Python
License	MIT — OSI-approved
Stars	5.5k
Forks	1.3k
Open issues	259
Latest release	v0.21.1 (2026-04-10)
Last updated	2026-07-08
Source	https://github.com/sooperset/mcp-atlassian

What mcp-atlassian is

A Python MCP server exposing Atlassian REST APIs through standardized MCP tool interfaces, supporting both basic auth (Cloud: API tokens; Server/DC: PATs) and OAuth 2.0. Implements SSE and HTTP transport modes, compatible with Jira 8.14+ and Confluence 6.0+, with environment-variable-driven configuration.

Quickstart

Get the mcp-atlassian source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/sooperset/mcp-atlassian.git2cd mcp-atlassian3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

AI-Assisted Issue Management & Ticket Creation

Enable Claude or Cursor to search Jira with JQL, retrieve issue details, create/update tickets, and transition workflows directly from your IDE—automating routine ticket operations without manual Atlassian portal switching.

Documentation Search & Content Integration

Let AI assistants query Confluence pages, extract onboarding docs, and retrieve institutional knowledge in real time, reducing manual wiki navigation and enabling context-aware responses during development.

Enterprise Workflow Automation

Build custom integrations or multi-tool orchestration (via MCP composition) to sync Jira updates with external systems, generate reports, or enforce approval workflows across Server/Data Center deployments.

Implementation considerations

API token and authentication credential management: store securely (e.g., environment variables, secret managers), never commit to repos; audit token access and rotation policies per your security requirements.
Rate limiting: Atlassian Cloud imposes API rate limits (typically 30 req/min for Cloud, higher for Server/DC); batch queries and implement backoff logic if heavy concurrent AI usage is expected.
Field mapping and permissions: ensure the service account (API token owner) has sufficient Jira/Confluence permissions; custom fields may require schema inspection to avoid create/update failures.
Network latency: MCP over HTTP/SSE may introduce 100-500ms per tool invocation; bundle queries where possible and set appropriate timeouts in your AI client configuration.
Version compatibility: verify your Jira (8.14+) and Confluence (6.0+) versions and test PAT/OAuth flows for Server/Data Center before production rollout.

When to avoid it — and what to weigh

Highly Custom Atlassian Plugins Required — If your workflows depend on bespoke Atlassian plugins, advanced add-ons, or deeply customized Jira/Confluence configuration not exposed via REST APIs, mcp-atlassian will not reach those features.
Real-Time Bi-Directional Sync Needed — This tool is optimized for AI-agent-initiated queries and actions. If you need webhooks, event streaming, or real-time syncing of changes from Atlassian back to other systems, consider a dedicated integration platform.
Offline or Air-Gapped Deployments — mcp-atlassian requires live network access to Atlassian instances. If your Jira/Confluence is offline or behind a restrictive firewall without outbound routes, deployment will fail.
No Audit or Security Monitoring — The tool logs API token usage in environment variables and .env files. If your compliance policy forbids storing plaintext credentials or requires encrypted secret management, additional hardening is mandatory.

License & commercial use

MIT License. Permits commercial use, modification, and distribution with minimal restrictions. Requires inclusion of license and copyright notice.

MIT is a permissive OSI-approved license and explicitly allows commercial use. No restrictions on charging for products or services that incorporate mcp-atlassian. However, verify that your use of Atlassian APIs complies with Atlassian's own terms of service and licensing agreements.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Low
DEV.co fit	Strong
Assessment confidence	High

Security considerations

API tokens stored in environment variables and .env files; ensure .env is not committed to version control and access is restricted to authorized personnel. Service account permissions should be least-privilege (read-only where possible). OAuth 2.0 support available for higher-security scenarios. No mention of encrypted credential storage or secret rotation tooling; review SECURITY.md for best practices. MCP transport (stdio vs. HTTP) impacts attack surface—HTTP modes require TLS and authentication review. No security audit or penetration test data provided.

Alternatives to consider

Atlassian REST API + Custom Integrations

Direct API calls give full control and no abstraction layer, but require custom SDKs/scripting and lose MCP standardization; useful if you don't need AI-agent integration.

Zapier / Make (Integromat)

Low-code automation platforms with Jira/Confluence connectors; easier for non-technical users but lack real-time AI context and deeper customization than mcp-atlassian.

Atlassian Server/Cloud SDKs (Java, Python)

Native SDKs for programmatic access; greater feature parity with Atlassian APIs but require application development, not suitable for AI-agent-in-IDE workflows.

Software development agency

Build on mcp-atlassian with DEV.co software developers

Review the authentication and configuration docs, set up your API token, and configure mcp-atlassian in your MCP settings. Start with a read-only query to validate connectivity, then expand to ticket creation and workflow automation.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

atlassian-mcp-server mcp google_workspace_mcp

Related on DEV.co

Explore the category and the services that help you build with it.

MCP Servers API Development Enterprise Software AI Application Development Talk to DEV.co

mcp-atlassian FAQ

Does mcp-atlassian work with both Atlassian Cloud and Server/Data Center?

Yes. Cloud uses API tokens (OAuth 2.0 supported); Server/Data Center uses Personal Access Tokens (PAT). See Authentication docs for setup differences.

What happens if my Atlassian API token expires or is rotated?

The MCP server will fail authentication until you update the environment variable. Implement token rotation policies and monitor logs for auth failures.

Can I use mcp-atlassian without Claude or Cursor?

Yes, mcp-atlassian is an MCP server and can work with any MCP client. However, tight IDE integration (Claude Desktop, Cursor) is the primary use case.

Are there rate limits I should be aware of?

Atlassian Cloud typically limits to 30 req/min per API token; Server/Data Center limits vary. Batch queries and implement backoff if high concurrency is needed.

Custom software development services

Adopting mcp-atlassian is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate mcp servers software in production.

Ready to Connect Your AI Assistant to Jira & Confluence?

Talk to DEV.co Schedule a Consultation