MTS synchronizes a MongoDB-backed Kanban workflow across two interfaces:
- An MCP server for AI-assisted task operations
- A Pixoo 64 display that cycles through live task cards
This project has two main apps:
- Kanban_MCP: TypeScript MCP server for task creation, status updates, priority updates, tags, and analytics prompts.
- Interface: Python app that reads tasks from MongoDB and renders them on a Pixoo device.
Both apps share the same MongoDB collections, so changes made through MCP are reflected in the Pixoo display.
- Create and manage tasks through MCP tools
- Move tasks across todo, inProgress, and done
- Add task tags and set task priority
- Request task analytics from an MCP prompt
- Display todo and in-progress tasks on Pixoo
- Shared root environment config through .env
- Kanban_MCP: MCP server source and build output
- Interface: Pixoo display interface
- mets_install.py: Dependency install and MCP build helper
- mcp.json: VS Code MCP server config
The MongoDB containing the tasks is from one of my other project kanban. This program can only work on a DB with the same document.
The Schema are as follows:
const taskSchema = new mongoose.Schema({
title: String,
description: String,
taskStatus: String,
createdAt: {
type: Date,
immutable: true,
default: () => Date.now(),
},
updatedAt: Date,
user: {
type: mongoose.Schema.Types.ObjectId,
ref: "User",
},
});const userSchema = new mongoose.Schema({
username: String,
email: String,
password: String,
tasks: [{
type: mongoose.Schema.Types.ObjectId,
ref: "Task",
}],
createdAt: {
type: Date,
immutable: true,
default: () => Date.now(),
},
updatedAt: {
type: Date,
default: () => Date.now(),
},
});Create or update .env in the repository root with
MONGODB_URI=your_mongodb_connection_string
DB_NAME=your_database_name
USER_NAME=your_username_for_interface
PIXOO_IP=your_pixoo_device_ip
KANBAN_USERNAME=${USER_NAME}python3 mets_install.pyDefined in index.ts:
- Tool: create-task
- Tool: move-task
- Tool: set-prioity
- Tool: add-tag
- Resource: tasks://all
- Prompt: tasks-analytics
- Backend: TypeScript, Node.js, MCP SDK
- Frontend: Python, Pixoo API
- Database: MongoDB, Mongoose
- TypeScript/Node.js development
- Python scripting
- MongoDB and Mongoose ODM
- MCP (Model Context Protocol) server implementation
- REST API design
- Device integration (Pixoo 64 API)
- Kanban workflow patterns