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Official remote MCP server for Atlassian. Securely connect Jira, Confluence, Jira Service Management, Bitbucket, and Compass to Claude, ChatGPT, Cursor, VS Code, and other AI tools using OAuth 2.1 or API tokens.
This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.
100
review score
Problem solved
It solves the problem of securely connecting AI agents to enterprise Atlassian data without exposing API keys or managing complex authentication flows. Unlike generic MCP servers, it provides a pre-built, Atlassian-maintained integration with OAuth 2.1 support, reducing development overhead for teams wanting AI-powered access to their project management and collaboration tools.
Deployment reality
The available setup signal starts with: Pick your AI client below to install the official Atlassian Rovo MCP Server.. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is Apache-2.0. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
Developers can build AI assistants that query Jira issues, fetch Confluence pages, manage service desk tickets, browse Bitbucket repositories, and navigate Compass components. Real-world use cases include automated project status updates, AI-driven documentation search, incident response triage, and code review assistance. The ceiling is limited only by the Atlassian APIs—essentially any action available via the Atlassian REST APIs can be exposed to AI agents.
Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.
atlassian/atlassian-mcp-server is tracked as a JavaScript project in the AI Agent, MCP Server, LLM Tool, AI App, Infrastructure area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 905 total stars, with +0 today, +36 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Moderate; the latest push was 97 days ago, and the open issue queue is 69, about 7.62% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 115 forks and 905 watchers suggest how often the project is reused or followed. License signal: Apache-2.0. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need AI prototypes, LLM workflows, and agent-style applications. Be cautious when you need a legal review, security audit, or production SLA.
Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 36. Follow the original GitHub repository for final install, security, and release information.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
ReadyRepository metadata and README/source references are attached.
License
ReadyApache-2.0 is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
905 Stars
Reuse
115 Forks
Attention
905 Watchers
Maintenance
moderate
License
Apache-2.0
Open issues
69
The official Atlassian Rovo MCP Server is a cloud-hosted bridge that gives AI tools secure, real-time access to Jira, Confluence, Jira Service Management, Bitbucket, and Compass data using the Model Context Protocol.
Key Features
- Summarize and search Jira, Confluence, Jira Service Management, and Bitbucket content without switching tools. - Create and update issues or pages based on natural language commands. - Automate repetitive work like generating tickets from meeting notes or specs.
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
MCP Server
Model Context Protocol servers, clients, and integrations
LLM Tool
Libraries and tools for LLM apps, RAG, prompts, and evals
AI App
End-user AI applications and AI-native product examples
Infrastructure
Cloud, deployment, networking, containers, and platform tooling
Pick your AI client below to install the official Atlassian Rovo MCP Server.55
Health Score
Moderate
Commit Activity
Aug 1, 2025
Created
Jul 8, 2026
Last push
Star history will appear after daily syncs accumulate data.
Forks
Open
Watchers
atlassian
GitHub profilefreeCodeCamp/freeCodeCamp
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Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
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A list of Free Software network services and web applications which can be hosted on your own servers
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An agentic skills framework & software development methodology that works.
react/react
The library for web and native user interfaces.
✓
License
✓
Forked
~ Moderate
Maintained
Problem Solved
It solves the problem of securely connecting AI agents to enterprise Atlassian data without exposing API keys or managing complex authentication flows. Unlike generic MCP servers, it provides a pre-built, Atlassian-maintained integration with OAuth 2.1 support, reducing development overhead for teams wanting AI-powered access to their project management and collaboration tools.
Capabilities
Developers can build AI assistants that query Jira issues, fetch Confluence pages, manage service desk tickets, browse Bitbucket repositories, and navigate Compass components. Real-world use cases include automated project status updates, AI-driven documentation search, incident response triage, and code review assistance. The ceiling is limited only by the Atlassian APIs—essentially any action available via the Atlassian REST APIs can be exposed to AI agents.
Bottom Line
This is ideal for teams already using Atlassian products who want to integrate AI agents for productivity. It should be avoided by those not using Atlassian or needing on-premise solutions. The key trade-off is convenience vs. dependency: you gain a secure, ready-made bridge but are locked into Atlassian Cloud and its API rate limits.