io.github.rog0x/task MCP Server

This Model Context Protocol (MCP) server provides task and project management tools for AI agents. It focuses on todo tracking, priority handling, estimation, and burndown, with tool support for creating and updating tasks and sorting them using established prioritization frameworks.

🛠️ Key Features

Task and project management for AI agents
Todo, priority, estimation, and burndown
In-memory task list management (add, complete, update status, delete, list)
Filtering by status, priority, and tags
Session-limited data persistence

🚀 Use Cases

Automating standup-style task updates via AI agents
Prioritizing task backlogs using standard frameworks
Generating or maintaining burndown-oriented views from task data

⚡ Developer Benefits

Tooling implemented for TypeScript-based MCP server usage
Priority sorting supports:
- Eisenhower Matrix (urgent/important quadrants)
- RICE Scoring (Reach, Impact, Confidence, Effort)
- MoSCoW Method (Must Have, Should Hav)

⚠️ Limitations

Task data is in-memory and persists only within the session.

Tools

todo_manager

In-memory task list management. Add, complete, update status, delete, and list tasks with filtering by status, priority, and tags. Data persists within the session.

priority_sorter

Sort tasks using established prioritization frameworks:

Eisenhower Matrix — categorize by urgent/important into four quadrants (Do First, Schedule, Delegate, Eliminate)

RICE Scoring — rank by Reach, Impact, Confidence, and Effort

MoSCoW Method — classify as Must Have, Should Have, Could Have, or Won't Have

time_estimator

Estimate task duration using PERT methodology. Break work into subtasks, provide optimistic/realistic/pessimistic estimates, and get weighted expected time with configurable buffer.

standup_generator

Generate daily standup updates from the current task list. Outputs yesterday (completed), today (in progress), and blockers with summary statistics.

burndown_calculator

Calculate sprint burndown data. Given tasks with story points and sprint duration, computes ideal vs actual burndown, velocity metrics, and completion forecast.

io.github.rog0x/task