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Backlog.md

calendar_todayAdded Jan 27, 2026
categoryAgent & Tooling
codeOpen Source
TypeScriptNode.jsAI AgentsWeb ApplicationCLIAgent & ToolingDeveloper Tools & CodingEnterprise Applications & Office

A markdown-native task manager and Kanban visualizer designed for any Git repository, facilitating project collaboration between humans and AI agents.

One-minute overview#

Backlog.md turns any folder with a Git repo into a self-contained project board powered by plain Markdown files and a zero-config CLI. Whether you're an individual developer or a team, you can use it to manage project tasks while collaborating seamlessly with AI agents.

Core value: Complete local task management through Markdown files without requiring cloud services, while supporting integration with multiple AI tools.

Getting Started#

Installation difficulty: Low - Simple command-line installation gets you started quickly

# Installation command
npm i -g backlog.md
# or
bun add -g backlog.md
# or
brew install backlog-md

Is this suitable for me?

  • Individual developers/small teams: Need a completely local, cloud-service-free task management tool
  • AI-assisted development: Want to collaborate with AI agents like Claude, Gemini on projects
  • Complex project management: If you need advanced features like Gantt charts, resource allocation, you might need more specialized project management software
  • Large team collaboration: While it supports multiple users, it doesn't have the complex permissions and auditing features of enterprise project management software

Core Capabilities#

1. Markdown-native task management - Streamlined documentation#

  • Each task is a standalone .md file stored in the backlog folder
  • File format: task-<task-id> - <task-title>.md for easy identification and management Real value: Task documentation happens automatically without extra steps, seamlessly integrating with existing Git workflows

2. AI collaboration capabilities - Human-AI development partnership#

  • Supports multiple AI agents including Claude Code, Gemini CLI, Codex
  • Deep integration with task management through the Model Context Protocol (MCP) Real value: AI agents can directly understand, create, and execute tasks, enabling automated development workflows

3. Dual interface experience - Flexible working methods#

  • Terminal board: backlog board command displays a live board in your terminal
  • Modern web interface: backlog browser launches a responsive web UI for visual task management Real value: Choose the interface that best fits your environment and preferences, boosting productivity

4. Powerful search and querying - Quickly find information#

  • Fuzzy search functionality across tasks, documents, and decisions
  • Rich query commands supporting filtering by status, priority, assignee, and more Real value: Quickly locate needed information among many tasks, improving project discoverability

5. Task dependency management - Clear workflows#

  • Supports task dependency setup with circular dependency prevention
  • Visual execution sequences clearly showing relationships between tasks Real value: Properly prioritize and sequence tasks to avoid work conflicts

Tech Stack & Integration#

Development language: TypeScript/JavaScript Main dependencies: Built on Node.js, installable via npm, bun, or Homebrew Integration method: CLI tool + Web interface + MCP protocol (for AI integration)

Ecosystem & Extensions#

  • Plugins/Extensions: Integrates with various AI agents through the MCP protocol including Claude Code, Gemini CLI, Codex
  • Integration capabilities: Fully integrated with Git workflows, all data stored as Markdown files in the local repository

Maintenance Status#

  • Development activity: Actively developed with support for multiple installation methods and continuous AI tool integration
  • Recent updates: Includes complete MCP integration guide, showing developers are actively following AI tool developments
  • Community response: Provides detailed documentation and examples, indicating focus on user experience

Commercial & Licensing#

License: MIT

  • ✅ Commercial: Commercial use allowed
  • ✅ Modification: Code modification allowed
  • ⚠️ Restrictions: Must include original license notice and copyright information

Documentation & Learning Resources#

  • Documentation quality: Comprehensive with detailed CLI reference and integration guides
  • Official documentation: Detailed README and documentation included in the GitHub repository
  • Example code: Complete command-line usage examples and web interface screenshots provided

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