task-orchestrator
An MCP server that manages features and tasks across multiple projects. Useful for having the AI take PRD documents, breaking them into features and tasks for use across multiple interactions.
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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.
📚 Documentation
- 📖 Full Documentation - Complete guides and reference
- 🚀 Quick Start Guide - Get running in 2 minutes
- 🔧 API Reference - All 37 MCP tools detailed
- 📋 Workflow Prompts - 5 built-in workflow automations
- 📝 Templates - 9 built-in documentation templates
- 🗃️ Database Migrations - Schema change management for developers
- 💬 Community Wiki - Examples, tips, and community guides
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 creationtask_breakdown_workflow- Complex task decompositionbug_triage_workflow- Systematic bug managementproject_setup_workflow- Complete project initializationimplement_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=trueand check logs inlogs/ - 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
- Fork the repository
- Create a feature branch
- Make your changes with tests
- Submit a pull request
See contributing guidelines for details.
License
k8s-ai is an AI-powered management system for Kubernetes. Users can perform real-time diagnostics, resource monitoring, and smart log analysis by asking questions in natural language. This simplifies Kubernetes management, eliminating the need to memorize commands and providing a modern alternative.