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Backlogr MCP Server

by scottiesan

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

  1. LLM-Assisted Planning: ChatGPT/Claude can help structure entire projects by creating epics, stories, and tasks
  2. Automated Development: Coding agents pull tasks, implement features, and mark them complete
  3. Team Coordination: Multiple agents can work on the same project without conflicts
  4. 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

  1. Install Dependencies:
    npm install
  2. Configure Environment: Copy .env.example to .env and set your Supabase credentials:
    cp .env.example .env
  3. Start Development Server:
    npm run dev
  4. 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 projects
  • tasks - Individual work items with priorities and status
  • requirements - Functional requirements
  • project_members - Team member access control
  • task_requirements - Linking table between tasks and requirements

Development

# Build for production npm run build # Start development server with hot reload npm run dev

License

ISC License - see package.json for details

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security - not tested
F
license - not found
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quality - not tested

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.

  1. Core Capabilities
    1. 🎯 AI-Powered Project Planning
    2. 🤖 MCP Integration for Coding Agents
    3. 🔧 Technical Architecture
  2. Key Features
    1. For Project Managers & LLMs:
    2. For Development Agents:
  3. Use Cases
    1. Integration Ready
      1. Quick Start
        1. API Endpoints
          1. Database Schema
            1. Development
              1. License

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