"Official Atlassian MCP Server by Atlassian" matching MCP servers:

Enables Claude Code to use a filtered subset of Atlassian Rovo MCP tools for Jira and Confluence, automatically injecting required parameters and stripping noisy fields to reduce token usage.

Enables natural-language interaction with self-hosted Jira and Bitbucket, providing tools for ticket management, pull requests, code review, and git context.

Enables AI assistants to interact with Jira by executing commands through the Atlassian CLI. It supports searching issues with JQL, managing comments, updating statuses, and handling issue assignments through natural language.

Integrates with Atlassian Cloud products (Confluence and Jira) to enable AI assistants to search, read, create, and manage pages, issues, comments, attachments, and export content through natural language interactions.

Browser-backed MCP wrapper for mcp-atlassian with Playwright SSO auth. Enables AI tools to access Atlassian Server/Data Center instances behind corporate SSO (Okta, SAML, ADFS) where API tokens are not available

A Model Context Protocol server for Atlassian Jira and Confluence that supports both Cloud and On-Prem/Data Center deployments. It enables AI assistants to search, create, and manage issues and pages using secure authentication methods like PAT and OAuth.

An MCP server that integrates with Jira and Confluence to enable AI-powered issue management, content search, and document creation. It supports both Cloud and on-premise deployments, allowing users to automate workspace tasks through natural language.

An MCP server that enables AI assistants to interact with Atlassian Jira and Confluence across Cloud and Server/Data Center environments. It supports tasks like searching and summarizing documentation, managing Jira issues, and creating content through natural language.

Provides integration with Atlassian products through the Model Context Protocol, allowing users to interact with JIRA tickets and Confluence pages.

Enables coding agents to search and read Jira Cloud issues with read-only, per-project access controls while keeping the API token in the OS keychain.

Managed Code Plugin for Cursor IDE providing integration with Atlassian products (JIRA, Confluence, BitBucket), enabling developers to search for tasks, create new issues, view documentation, and manage code repositories directly from the IDE.

An open-source Model Context Protocol (MCP) server for Atlassian Jira and Confluence Cloud, enabling LLMs to search, read, write, and manage issues and pages.

Enables AI assistants to interact with Atlassian Bamboo CI/CD, allowing natural language queries to check build status, fetch logs, trigger builds, and manage deployments.

Enables IntelliJ IDE users to interact with Confluence pages via natural language, including searching, summarizing, analyzing content and diagrams, reviewing docs, and rephrasing text using GitHub Copilot AI.

An MCP server for interacting with Atlassian Jira, enabling issue management, attachments, and other operations via natural language.

Enables one agent session to work across many Jira Cloud sites at once, routing each request by issue-key prefix so users can fetch and search issues, manage comments, and download or upload attachments directly to disk instead of shuffling base64 through chat context.

Enables AI assistants to interact with Atlassian Bitbucket Cloud workspaces, repositories, and pull requests through MCP tools for listing, getting, commenting, searching, and managing version control workflows.

Enables AI systems to interact with Atlassian Bitbucket Server/Data Center for accessing projects, repositories, branches, files, and managing pull requests.

Enables AI assistants to interact with Atlassian Bitbucket Cloud workspaces, repositories, branches, commits, pull requests, issues, pipelines, and deployments through generic API tools and repository cloning. Supports natural-language code search, review, commenting, and workflow automation via the MCP interface.

An MCP server that provides integration with Jira and Confluence for managing issues, boards, sprints, and documentation pages. It is specifically designed for native deployment on Heroku to enable AI models to interact with Atlassian resources using standardized tools.

An integration tool that enables AI assistants like Claude to directly access and interact with Bitbucket repositories, pull requests, and code without requiring copy/paste operations.

Enables AI assistants to interact with Bitbucket Cloud and self-hosted instances for pull request reviews, code search, repository operations, and managing PR comments and approvals.

A comprehensive MCP server for Jira, Confluence, and Bitbucket that supports both Cloud and Data Center deployments. It provides 136 tools for managing issues, searching documentation, and handling Git workflows like pull requests and pipelines.

Enables AI assistants to connect to Bitbucket Cloud and interact with workspaces, repositories, branches, commits, files, and pull requests through MCP tools, including listing, getting, creating, commenting, searching, reviewing, approving, declining, and merging PRs.

Enables AI assistants to read and manage Bitbucket Cloud workspaces, repositories, pull requests, branches, commits, and code through tools exposed over the standard MCP interface.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, branches, commits, and pull requests through generic API tools for reading, creating, commenting, searching, comparing, and managing resources. It supports natural-language version control workflows using scoped API tokens or app passwords.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, pull requests, commits, branches, diffs, comments, issues, pipelines, and deployments through MCP tools for listing, reading, creating, updating, deleting, searching, commenting, and cloning via the Bitbucket API.

Enables AI assistants and LLMs to interact with Bitbucket Cloud workspaces, repositories, and pull requests via tools for listing, getting, commenting, searching, and cloning. Connects AI directly to version control workflows through the standard MCP interface.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, pull requests, branches, commits, and code through MCP tools for listing, retrieving, searching, commenting, managing PRs, and cloning repositories.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, branches, commits, and pull requests through generic GET, POST, PUT, PATCH, DELETE, and clone tools, including reading PR diffs, adding comments, approving, merging, and filtering responses with JMESPath. It connects LLMs directly to version control workflows so tasks like code review, repository search, and PR management can be done in natural language.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, branches, commits, and pull requests through tools for listing, retrieving, creating, commenting, searching, and cloning via the Bitbucket REST API.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, and pull requests by providing MCP tools for listing, reading, creating, commenting, searching, and cloning.

Connects AI assistants like Claude to Jira projects, enabling natural language queries and operations for issue management, project tracking, comments, and workflows through the Jira REST API.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, and pull requests through generic GET, POST, PUT, PATCH, DELETE, and clone tools, covering branches, commits, file contents, diffs, issues, pipelines, and deployments. Supports JMESPath filtering and a token-efficient output format to reduce token costs.

Enables AI assistants to work with Bitbucket Cloud workspaces, repositories, branches, commits, and pull requests — listing, creating, commenting, comparing diffs, searching code, and cloning repos — through natural language. It exposes generic GET/POST/PUT/PATCH/DELETE/clone tools with JMESPath filtering and a token-efficient output format for LLM workflows.

Enables AI assistants to interact with Bitbucket workspaces, repositories, branches, commits, and pull requests through MCP tools for listing, retrieving, commenting, searching, and managing version control workflows. It supports generic GET, POST, PUT, PATCH, DELETE, and clone operations against Bitbucket Cloud REST API endpoints.

Enables AI assistants to interact with Bitbucket workspaces, repositories, branches, commits, and pull requests for listing, retrieving, searching, commenting, comparing, and automating version control workflows.

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, pull requests, branches, commits, and code through MCP tools for reading, creating, updating, deleting, commenting, searching, and cloning.

Enables AI assistants to access and manage Bitbucket Cloud workspaces, repositories, branches, commits, and pull requests through MCP tools for listing, retrieving, searching, commenting, cloning, and other version-control workflows.

Enables AI assistants to read and manage Bitbucket workspaces, repositories, branches, commits, files, and pull requests through the Bitbucket Cloud REST API, including commenting, approving, merging, comparing branches, and cloning repos. It exposes generic GET, POST, PUT, PATCH, and DELETE tools with JMESPath filtering and token-efficient output for any endpoint.