Local PM

A lightweight, self-hosted project management tool with a built-in MCP (Model Context Protocol) server that enables AI assistants to manage your projects, tickets, and teams directly.

Features

• Kanban Board - Drag-and-drop ticket management with Todo, In Progress, and Done columns
• Projects - Organize work with customizable projects (icons, colors, prefixes)
• Teams - Assign tickets to teams for better organization
• Tickets - Full-featured tickets with:
  • Priority levels (Urgent, High, Medium, Low)
  • Due dates
  • Custom labels with colors
  • Subtasks with completion tracking
  • Ticket dependencies (blocked by)
  • Rich text descriptions
• MCP Server - AI-native project management via Model Context Protocol
• Self-Hosted - Your data stays on your machine
• Docker Ready - One command deployment

Screenshots

Kanban Board

Tickets

Projects

Teams

Installation

Using Docker (Recommended)

1. Clone the repository:

git clone https://github.com/your-username/local-pm.git
cd local-pm

2. Start the containers:

docker-compose up -d

3. Access the app at http://localhost:3010

Manual Installation

1. Clone the repository and install dependencies:

git clone https://github.com/your-username/local-pm.git
cd local-pm
npm install

2. Set up environment variables:

cp .env.example .env
# Edit .env with your MongoDB connection string

3. Run the development server:

npm run dev

MCP Server Setup

The MCP (Model Context Protocol) server allows AI assistants like Claude to interact with your project management data directly.

Building the MCP Server

cd mcp-server
npm install
npm run build

Adding to Claude Code (Global)

claude mcp add --scope user local-pm node "/path/to/local-pm/mcp-server/dist/index.js"

Adding to Claude Desktop

Add to your Claude Desktop config (~/.claude/claude_desktop_config.json):

{
  "mcpServers": {
    "local-pm": {
      "command": "node",
      "args": ["/path/to/local-pm/mcp-server/dist/index.js"],
      "env": {
        "LOCAL_PM_URL": "http://localhost:3010"
      }
    }
  }
}

MCP Tools Reference

The MCP server exposes 18 tools for complete project management:

Project Tools

Tool	Description
list_projects	List all projects with optional status filter
get_project	Get detailed project information by ID
create_project	Create a new project with name, prefix, icon, color
update_project	Update project properties
delete_project	Delete a project and optionally all its tickets

Team Tools

Tool	Description
list_teams	List all teams
get_team	Get detailed team information by ID
create_team	Create a new team
update_team	Update team properties
delete_team	Delete a team

Ticket Tools

Tool	Description
list_tickets	List tickets with filters (project, team, status, priority)
get_ticket	Get detailed ticket information by ID
create_ticket	Create a new ticket with full properties
update_ticket	Update ticket properties
move_ticket	Move ticket to different status column
delete_ticket	Delete a ticket

Board & Subtask Tools

Tool	Description
get_board	Get full Kanban board grouped by status
toggle_subtask	Toggle subtask completion status
add_subtask	Add a subtask to a ticket

How MCP Enhances AI Development

What is MCP?

Model Context Protocol (MCP) is an open standard that enables AI assistants to interact with external tools and data sources. Instead of just chatting, AI can take actions in the real world through well-defined tool interfaces.

Benefits for AI-Assisted Development

1. Persistent Task Tracking

   • AI can create tickets for features it's implementing
   • Track progress across coding sessions
   • Never lose context on what was done or what's pending

2. Structured Workflow

   • AI breaks down complex features into subtasks
   • Sets priorities and due dates
   • Manages dependencies between tickets

3. Project Organization

   • AI can organize work into logical projects
   • Assign tasks to teams
   • Maintain a clear overview of all work

4. Seamless Integration

   • Works directly in your AI coding workflow
   • No context switching to external tools
   • AI reads and updates tickets as it works

Example Workflow

You: "Create a project for our new authentication system"

AI: [Creates project AUTH with relevant description]

You: "Break down the login feature into tickets"

AI: [Creates tickets for:
  - AUTH-1: Implement login form UI
  - AUTH-2: Create authentication API endpoint
  - AUTH-3: Add JWT token handling
  - AUTH-4: Implement session management
  Sets AUTH-2 as blocking AUTH-3 and AUTH-4]

You: "Start working on the login form"

AI: [Moves AUTH-1 to In Progress, implements the feature,
     then moves to Done when complete]

Why Local & Self-Hosted?

• Privacy: Your project data stays on your machine
• Speed: No network latency for AI tool calls
• Control: Customize and extend as needed
• Offline: Works without internet connection

Tech Stack

• Frontend: Next.js 15, React, Tailwind CSS
• Backend: Payload CMS 3.0
• Database: MongoDB
• MCP Server: TypeScript, @modelcontextprotocol/sdk

Special Thanks

Built with Payload CMS