Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.
Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.
MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.
Enables an MCP-capable coding agent to run a local-first job search: recording verified opportunities in a private SQLite tracker, tracking follow-ups and outcomes, and preparing evidence-based resumes, application answers, and outreach drafts. It keeps all personal data on the user's machine and stops before submitting applications, uploading documents, or contacting anyone.
A Model Context Protocol (MCP) server that connects AI assistants to Jira Server/Data Center, enabling issue management, JQL search, sprint tracking, and natural language interaction with Jira.
Enables AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.
A JSON-based database MCP server with JWT authentication that enables user management, project tracking, department analysis, meeting management, and equipment tracking. Integrates with Claude Desktop to provide secure CRUD operations and analytics through natural language commands.
MCP servers for self-hosted Atlassian Data Center (Jira, Confluence, Bitbucket) enabling AI assistants to search, manage, and interact with issues, pages, and pull requests.
Exposes the WCC event, mentorship, and analytics pipeline tools as MCP endpoints with per-group authentication and dry-run support, enabling agents to manage events, mentors, and analytics.
MCP server that connects to Jira Data Center, enabling issue search, retrieval, creation, comments, workflow transitions, project listing, arbitrary JQL, and turning meeting notes into structured Jira stories, tasks, and bugs.
Enables AI assistants to deeply introspect Jira Data Center configurations — including workflows, schemes, automation, and Assets — through 76 read-only tools, without any modification capability.
Exposes RE-Butler knowledge and validation tools for hybrid semantic search, requirement templates, user story validation, and Azure DevOps work item creation with approval gates.
Enables LLMs to interact with Atlassian Jira Data Center through natural language queries for semantic search and automated workflow execution. It provides secure tools to discover, inspect, and execute Jira API operations using production-ready authentication methods.