Hey @roocode community!
I'm thrilled to share a project born from my work with Roocode and the vision of an AI-powered development team: the Anubis MCP Server!
This system is heavily inspired by Roocode and designed to orchestrate an AI development workflow based on agile methodology. It simulates
Provides a task passport system for handoff across AI harnesses, enabling users to list, open, create, and checkpoint tasks with stable IDs and verified state.
Enables intelligent task management with status tracking, dependency resolution, and automatic next task discovery based on preconditions and priorities. Supports hierarchical task structures with subtasks and flexible JSON-based configuration.
Enables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.
Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.
This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.
MCP Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.
Facilitates AI session handoffs and next steps tracking through project-based organization, supporting task prioritization and seamless workflow management.
Enables AI assistants to manage tasks through YAML-based storage with subtask suggestions, status updates, and Mermaid Gantt chart generation. Supports hierarchical task structures with attributes like dependencies, milestones, and parallel execution.
A campaign and task management MCP server for AI coding assistants, enabling dependency tracking, acceptance criteria, testing strategies, and progress monitoring for projects.
Provides specialized tools for portfolio health analysis, rebalance simulations, and trade execution via a single interface powered by MongoDB. It enables AI agents to manage investment portfolios while adhering to organizational governing rules, clearance guards, and rate limits.
A Model Context Protocol server providing comprehensive task management capabilities with support for project organization, task tracking, and automatic PRD parsing into actionable items.
Provides structured workflows (phases, gates, coordination) for AI agents, enabling complex task execution with quality enforcement and multi-agent coordination via Model Context Protocol.
An intelligent task management system that provides structured workflows for AI Agents to plan, decompose, and execute complex programming tasks. It features a dedicated research mode for technical investigations and a task memory function to optimize workflows and avoid redundant coding work.
An MCP server that transforms text into knowledge graphs and autonomously generates insights by combining Montague Grammar with Zettelkasten methodology.
Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce β the server blocks the call if they don't. Works with any MCP-compatible client.