task-orchestrator

MCP Task Orchestratorは、Kotlinで実装されたモデルコンテキストプロトコル(MCP)サーバーで、AIアシスタントがプロジェクトデータと効率的に対話するための構造化されたタスク管理を提供します。豊富なドキュメントとワークフロー自動化機能を備え、開発者にとっても使いやすい設計です。

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MCP Task Orchestrator

A Kotlin implementation of the Model Context Protocol (MCP) server for comprehensive task management, providing AI assistants with a structured, context-efficient way to interact with project data.

Version
License: MIT

📚 Documentation
Why Use MCP Task Orchestrator?
  • 🤖 AI-Native: Designed specifically for AI assistant workflows
  • 📊 Hierarchical Organization: Projects → Features → Tasks with dependencies
  • 🎯 Context-Efficient: Progressive loading and token optimization
  • 📋 Template-Driven: 9 built-in templates for consistent documentation
  • 🔄 Workflow Automation: 5 comprehensive workflow prompts
  • 🔗 Rich Relationships: Task dependencies with cycle detection
  • 🔒 Concurrent Access Protection: Built-in sub-agent collision prevention
  • ⚡ 37 MCP Tools: Complete task orchestration API
Quick Start (2 Minutes)
1. Pull or Build Docker Image
Option A: Production Image (Recommended)
# Pull latest release
docker pull ghcr.io/jpicklyk/task-orchestrator:latest

# Or specific version
docker pull ghcr.io/jpicklyk/task-orchestrator:1.0.1

# Or latest build from main branch
docker pull ghcr.io/jpicklyk/task-orchestrator:main
Option B: Build Locally (Development)
# Build locally
./scripts/docker-clean-and-build.bat  # Windows
# Or manually: docker build -t mcp-task-orchestrator:dev .
2. Configure Claude Desktop or Claude Code
For Claude Desktop

Add to your claude_desktop_config.json:

Production Configuration

{
  "mcpServers": {
    "task-orchestrator": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "--volume", "mcp-task-data:/app/data",
        "ghcr.io/jpicklyk/task-orchestrator:latest"
      ]
    }
  }
}

Local Development Configuration

{
  "mcpServers": {
    "task-orchestrator": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "--volume", "mcp-task-data:/app/data",
        "mcp-task-orchestrator:dev"
      ]
    }
  }
}
For Claude Code

Use the JSON configuration command:

# Production version (latest release)
claude mcp add-json task-orchestrator '{"type":"stdio","command":"docker","args":["run","--rm","-i","-v","mcp-task-data:/app/data","ghcr.io/jpicklyk/task-orchestrator:latest"]}'

# Specific version
claude mcp add-json task-orchestrator '{"type":"stdio","command":"docker","args":["run","--rm","-i","-v","mcp-task-data:/app/data","ghcr.io/jpicklyk/task-orchestrator:1.0.1"]}'

# Latest from main branch
claude mcp add-json task-orchestrator '{"type":"stdio","command":"docker","args":["run","--rm","-i","-v","mcp-task-data:/app/data","ghcr.io/jpicklyk/task-orchestrator:main"]}'

# Local development version (after building locally)
claude mcp add-json task-orchestrator '{"type":"stdio","command":"docker","args":["run","--rm","-i","-v","mcp-task-data:/app/data","mcp-task-orchestrator:dev"]}'
3. Test Connection (Optional)
# Test the Docker container runs correctly
docker run --rm -i -v mcp-task-data:/app/data ghcr.io/jpicklyk/task-orchestrator:latest

# Test MCP connection (requires Node.js)
node scripts/test-mcp-connection.js
4. Start Using

Ask Claude:

  • "Create a new project for my web application"
  • "Show me the project overview"
  • "Apply the technical approach template to this task"
Core Concepts
Project (optional)
  └── Feature (optional)
      └── Task (required) ←→ Dependencies → Task
          └── Section (optional, detailed content)
  • Projects: Top-level organizational containers
  • Features: Group related tasks into functional units
  • Tasks: Primary work units with status, priority, complexity
  • Dependencies: Relationships between tasks (BLOCKS, IS_BLOCKED_BY, RELATES_TO)
  • Sections: Rich content blocks for documentation
  • Templates: Standardized documentation patterns
Key Features
Template System (9 Built-in Templates)
  • AI Workflow Instructions: Git workflows, PR management, task implementation, bug investigation
  • Documentation Properties: Technical approach, requirements, context & background
  • Process & Quality: Testing strategy, definition of done
Workflow Prompts (5 Built-in Workflows)
  • create_feature_workflow - Comprehensive feature creation
  • task_breakdown_workflow - Complex task decomposition
  • bug_triage_workflow - Systematic bug management
  • project_setup_workflow - Complete project initialization
  • implement_feature_workflow - Git-aware feature implementation with completion validation
MCP Tools (37 Total)
  • 6 Task Management Tools - Core CRUD operations
  • 5 Feature Management Tools - Group related work
  • 5 Project Management Tools - Top-level organization
  • 3 Dependency Management Tools - Model relationships
  • 9 Section Management Tools - Rich documentation
  • 9 Template Management Tools - Workflow automation
Alternative Installation Options
Option 1: Direct JAR (Without Docker)
# Build
./gradlew build

# Run
java -jar build/libs/mcp-task-orchestrator-*.jar
Option 2: Development Environment Variables
# Configure environment for local development
MCP_TRANSPORT=stdio
DATABASE_PATH=data/tasks.db
USE_FLYWAY=true
MCP_DEBUG=true  # Enable debug logging
Configuration
Variable Description Default
MCP_TRANSPORT Transport type stdio
DATABASE_PATH SQLite database path data/tasks.db
USE_FLYWAY Enable Flyway database migrations true
MCP_SERVER_NAME Server name mcp-task-orchestrator
MCP_DEBUG Enable debug logging false
Release Information

Version follows semantic versioning with git-based build numbers:

  • Format: {major}.{minor}.{patch}.{git-commit-count}-{qualifier}
  • Stable releases remove the qualifier (e.g., 1.0.0.123)
  • Pre-releases include qualifier (e.g., 1.0.0.123-beta-01)

Current versioning defined in build.gradle.kts.

Development & Testing
# Run tests
./gradlew test

# Test MCP connection
node scripts/test-mcp-connection.js

# Debug mode
MCP_DEBUG=true java -jar build/libs/mcp-task-orchestrator-*.jar
Troubleshooting
Common Issues
  • JSON parsing errors: Enable MCP_DEBUG=true and check logs in logs/
  • Docker issues: Ensure Docker Desktop is running and docker volume inspect mcp-task-data
  • Connection problems: Test with the echo tool (see troubleshooting guide)
Getting Help
Contributing
  1. Fork the repository
  2. Create a feature branch
  3. Make your changes with tests
  4. Submit a pull request

See contributing guidelines for details.

License

MIT License

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