Uses Supabase as the backend database for storing and managing development projects, tasks, requirements, and team member access control with real-time capabilities.
Backlogr MCP Server
Backlogr is a Model Context Protocol (MCP) server designed to bridge the gap between AI development assistants (like ChatGPT and Claude) and project management workflows. It provides a standardized interface for LLMs to plan, create, and track development projects through a structured backlog system.
Core Capabilities
🎯 AI-Powered Project Planning
- Project Management: Create, list, fetch, and delete development projects
- Task Orchestration: Full CRUD operations for tasks with prioritization (P0-P3) and status tracking
- Requirements Management: Define and link functional requirements to development tasks
- Smart Search: Natural language search across projects, tasks, and requirements
🤖 MCP Integration for Coding Agents
- Standardized Interface: MCP-compliant tools that work with any MCP-enabled environment
- Task Assignment: Coding agents can pull development tasks directly from the backlog
- Context Awareness: Provides rich context about requirements and project scope
- Real-time Updates: Agents can update task status and progress as they work
🔧 Technical Architecture
- Built on MCP SDK: Leverages the official Model Context Protocol SDK for compatibility
- Supabase Backend: Scalable PostgreSQL database with real-time capabilities
- TypeScript Foundation: Type-safe development with comprehensive error handling
- RESTful API: Additional HTTP endpoints for web integration
Key Features
For Project Managers & LLMs:
- Project Creation: Start new development initiatives with structured backlogs
- Task Prioritization: Organize work with clear priority levels (P0-P3)
- Status Tracking: Monitor progress through Open → In Progress → Review → Done lifecycle
- Requirement Linking: Connect business requirements to implementation tasks
For Development Agents:
- Task Discovery: Search and fetch available development work
- Context Retrieval: Access complete project context including linked requirements
- Progress Reporting: Update task status and provide completion updates
- Collaboration: Work within team projects with proper access controls
Use Cases
- LLM-Assisted Planning: ChatGPT/Claude can help structure entire projects by creating epics, stories, and tasks
- Automated Development: Coding agents pull tasks, implement features, and mark them complete
- Team Coordination: Multiple agents can work on the same project without conflicts
- Progress Monitoring: Real-time visibility into what's being worked on and completed
Integration Ready
- MCP Standard: Works with any MCP client (Anthropic Claude, Cursor, etc.)
- Supabase Powered: Enterprise-grade database with authentication and real-time features
- Extensible: Easy to add new tools and capabilities as the MCP standard evolves
- Self-Hosted: Full control over your data and infrastructure
Quick Start
- Install Dependencies:
- Configure Environment:
Copy
.env.example
to.env
and set your Supabase credentials: - Start Development Server:
- Connect to MCP Client: Configure your MCP client (Claude, Cursor, etc.) to connect to the running server.
API Endpoints
The server provides both MCP tools and RESTful endpoints:
- MCP Tools:
search
,fetch
,backlogr_project
,backlogr_task
,backlogr_requirement
- HTTP API:
/messages
,/rpc
,/search
,/fetch
endpoints
Database Schema
The app uses a Supabase PostgreSQL database with tables for:
projects
- Development projectstasks
- Individual work items with priorities and statusrequirements
- Functional requirementsproject_members
- Team member access controltask_requirements
- Linking table between tasks and requirements
Development
License
ISC License - see package.json for details
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Enables AI assistants to create and manage development projects with structured backlogs, including tasks, requirements, and progress tracking. Provides a bridge between AI development assistants and project management workflows through standardized MCP tools.