keyurgolani/TasksMcp
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The MCP Task Manager is an advanced Model Context Protocol server designed to enhance task management for AI agents, providing features like complexity analysis, task breakdown, and seamless integration with AI environments.
MCP Task Manager
An intelligent Model Context Protocol (MCP) server that provides sophisticated task management capabilities for AI agents. Features automatic complexity analysis, task breakdown, persistent state management, and agent-friendly parameter preprocessing for seamless AI integration.
๐ค Agent-Friendly Features
The MCP Task Manager is specifically designed to work seamlessly with AI agents like Claude Desktop and Kiro IDE, including multi-agent orchestration environments where multiple AI agents work together on complex projects.
๐ Essential for AI Agents
All agents should review the for proven methodologies that maximize effectiveness:
- Plan and Reflect: Thorough planning before action, reflection after completion
- Use Tools, Don't Guess: Always investigate using available tools rather than making assumptions
- Persist Until Complete: Ensure all exit criteria are met before marking tasks complete
Key agent-friendly improvements include:
โจ Smart Parameter Preprocessing
- Automatic Type Conversion: Converts common agent input patterns before validation
- String numbers โ Numbers:
"5"
becomes5
- JSON strings โ Arrays:
'["tag1", "tag2"]'
becomes["tag1", "tag2"]
- Boolean strings โ Booleans:
"true"
becomestrue
,"yes"
becomestrue
- String numbers โ Numbers:
- Backward Compatible: Existing integrations continue to work without changes
- Performance Optimized: <50ms overhead per request
๐ฏ Enhanced Error Messages
- Visual Indicators: Clear error formatting with emojis (โ, ๐ก, ๐)
- Actionable Guidance: Specific suggestions on how to fix validation errors
- Tool-Specific Help: Context-aware error messages based on the tool being used
- Working Examples: Include actual usage examples in error responses
๐ค Multi-Agent Orchestration Support
- Task Dependencies: Set up complex task relationships with prerequisite management
- Ready Task Discovery: Find tasks that are unblocked and ready for parallel execution
- Agent Assignment: Orchestration agents can identify and assign ready tasks to specialized agents
- Parallel Execution: Multiple agents can work on independent tasks simultaneously
- Progress Tracking: Monitor completion status across distributed agent workflows
๐ง Common Agent Patterns Supported
// These all work seamlessly now:
{
"priority": "5", // String number โ 5
"tags": '["urgent", "important"]', // JSON string โ array
"includeCompleted": "true", // String boolean โ true
"estimatedDuration": "120" // String number โ 120
}
๐ Validation Improvements
- 80%+ Success Rate: For valid agent input patterns requiring conversion
- Clear Error Guidance: Non-technical error messages with helpful suggestions
- Enum Suggestions: Provides valid options when invalid choices are made
- Multiple Error Handling: Clear formatting when multiple validation issues occur
Before Agent-Friendly Updates:
Error: Expected number, received string at priority
After Agent-Friendly Updates:
โ priority: Expected number, but received string
๐ก Use numbers 1-5, where 5 is highest priority
๐ Example: 5 (highest) to 1 (lowest)
๐ง Common fixes:
1. Use numbers 1-5 for priority
Example: {"priority": 5}
๐ Quick Start
Method 1: Install via npx (Recommended)
The easiest way to get started - no local installation required:
# Test the installation
npx task-list-mcp@latest --version
# The server is now ready to use in your MCP client configuration
Method 2: Local Development Installation
For development or customization:
# Clone and install
git clone https://github.com/keyurgolani/task-list-mcp.git
cd task-list-mcp
npm install
# Build the project
npm run build
# Test that everything works
npx task-list-mcp@latest --version
โก Automatic MCP Client Setup
Use our setup script to automatically configure your MCP clients:
# Install the package
npx task-list-mcp@latest
This will automatically update your Claude Desktop or Kiro IDE configuration files.
๐ง Manual MCP Client Configuration
If you prefer manual configuration or the automatic setup doesn't work:
Claude Desktop Configuration
Add to your Claude Desktop mcp.json
configuration file:
macOS: ~/Library/Application Support/Claude/mcp.json
Windows: %APPDATA%/Claude/mcp.json
Linux: ~/.config/claude/mcp.json
{
"mcpServers": {
"task-manager": {
"command": "npx",
"args": ["task-list-mcp@latest"],
"env": {
"NODE_ENV": "production",
"MCP_LOG_LEVEL": "info",
"DATA_DIRECTORY": "~/.claude/task-manager-data"
}
}
}
}
Environment Variables Explained:
NODE_ENV
: Environment mode (development, production, test) - controls logging and error handlingMCP_LOG_LEVEL
: Logging verbosity (error, warn, info, debug) - set to "info" for normal operationDATA_DIRECTORY
: Directory for persistent data storage - will be created if it doesn't exist
Setup Validation:
- Save the configuration file
- Restart Claude Desktop
- Verify the task-manager server appears in available tools
- Test with: "Create a simple todo list to test the connection"
Kiro IDE Configuration
Add to your workspace .kiro/settings/mcp.json
:
{
"mcpServers": {
"task-manager": {
"command": "npx",
"args": ["task-list-mcp@latest"],
"env": {
"NODE_ENV": "production",
"MCP_LOG_LEVEL": "info",
"DATA_DIRECTORY": "/tmp/task-list-mcp-data"
},
"disabled": false,
"autoApprove": [
"create_list",
"get_list",
"list_all_lists",
"delete_list",
"add_task",
"update_task",
"remove_task",
"complete_task",
"set_task_priority",
"add_task_tags",
"search_tasks",
"filter_tasks",
"show_tasks",
"analyze_task",
"get_task_suggestions"
]
}
}
}
Environment Variables Explained:
NODE_ENV
: Environment mode (development, production, test) - controls logging and error handlingMCP_LOG_LEVEL
: Logging verbosity (error, warn, info, debug) - set to "info" for normal operationDATA_DIRECTORY
: Directory for persistent data storage - will be created if it doesn't exist
Auto-Approve Tools: All 15 available MCP tools are included for seamless AI agent integration. Remove tools from this list if you want manual approval for specific operations.
Setup Validation:
- Save the configuration file to
.kiro/settings/mcp.json
- Check the MCP Server view in the Kiro feature panel
- Verify the task-manager server shows as "Connected"
- Test with: "Create a todo list for testing the MCP connection"
Direct Command Line Usage
# Using npx
npx task-list-mcp@latest
# With options
npx task-list-mcp@latest --verbose
npx task-list-mcp@latest --config ./my-config.json
๐ง Environment Configuration
Core Environment Variables
The MCP Task Manager supports several environment variables to customize its behavior:
Variable | Required | Default | Description |
---|---|---|---|
NODE_ENV | No | development | Environment mode: development , production , or test |
MCP_LOG_LEVEL | No | info | Logging verbosity: error , warn , info , or debug |
DATA_DIRECTORY | No | ./data | Directory for persistent data storage |
STORAGE_TYPE | No | file | Storage backend: file or memory |
Environment-Specific Configuration Examples
Development Environment
{
"mcpServers": {
"task-manager": {
"command": "npx",
"args": ["task-list-mcp@latest"],
"env": {
"NODE_ENV": "development",
"MCP_LOG_LEVEL": "debug",
"DATA_DIRECTORY": "./dev-data",
"STORAGE_TYPE": "file"
}
}
}
}
Development Features:
- Verbose debug logging for troubleshooting
- Local data directory for easy access
- Enhanced error messages and stack traces
- Automatic data validation and consistency checks
Production Environment
{
"mcpServers": {
"task-manager": {
"command": "npx",
"args": ["task-list-mcp@latest"],
"env": {
"NODE_ENV": "production",
"MCP_LOG_LEVEL": "warn",
"DATA_DIRECTORY": "/var/lib/task-manager",
"STORAGE_TYPE": "file"
}
}
}
}
Production Features:
- Minimal logging for performance
- Secure data directory with proper permissions
- Optimized error handling
- Automatic backup and recovery mechanisms
Testing Environment
{
"mcpServers": {
"task-manager": {
"command": "npx",
"args": ["task-list-mcp@latest"],
"env": {
"NODE_ENV": "test",
"MCP_LOG_LEVEL": "error",
"DATA_DIRECTORY": "/tmp/test-data",
"STORAGE_TYPE": "memory"
}
}
}
}
Testing Features:
- Memory-only storage for fast test execution
- Minimal logging to reduce test noise
- Automatic cleanup between test runs
- Deterministic behavior for reliable testing
Environment Variable Details
NODE_ENV
Controls the overall behavior and optimization level:
development
: Enhanced debugging, verbose logging, development-friendly error messagesproduction
: Optimized performance, minimal logging, production-ready error handlingtest
: Fast execution, minimal output, deterministic behavior
MCP_LOG_LEVEL
Controls logging verbosity:
error
: Only critical errors (recommended for production)warn
: Errors and warnings (good balance for most use cases)info
: Errors, warnings, and informational messages (default)debug
: All messages including detailed debugging information (development only)
DATA_DIRECTORY
Specifies where persistent data is stored:
- Must be writable by the process running the MCP server
- Will be created automatically if it doesn't exist
- Should be backed up regularly in production environments
- Use absolute paths for production deployments
STORAGE_TYPE
Selects the storage backend:
file
: Persistent file-based storage with atomic operations (default)memory
: In-memory storage for testing and development (data lost on restart)
Configuration Troubleshooting
Common Configuration Issues
Server Won't Start
# Check if the command is accessible
npx task-list-mcp@latest --version
# Test with minimal configuration
NODE_ENV=development npx task-list-mcp@latest
Permission Errors
# Check directory permissions
ls -la /path/to/data/directory
# Create directory with proper permissions
mkdir -p ~/.local/share/task-manager
chmod 755 ~/.local/share/task-manager
Environment Variable Not Working
- Verify JSON syntax in configuration file
- Restart your MCP client after configuration changes
- Check client logs for environment variable parsing errors
- Test environment variables directly:
NODE_ENV=production MCP_LOG_LEVEL=debug npx task-list-mcp@latest --version
Data Directory Issues
# Verify directory exists and is writable
test -w /path/to/data/directory && echo "Writable" || echo "Not writable"
# Check disk space
df -h /path/to/data/directory
# Check for permission issues
ls -la /path/to/data/directory
Validation Steps
-
Test Configuration Syntax
# Validate JSON syntax cat ~/.config/claude/mcp.json | jq .
-
Verify Server Startup
# Test server starts with your configuration npx task-list-mcp@latest --version
-
Check Environment Variables
# Test with explicit environment variables NODE_ENV=production MCP_LOG_LEVEL=info npx task-list-mcp@latest --help
-
Validate Data Directory
# Ensure directory is accessible mkdir -p "$DATA_DIRECTORY" && echo "Directory OK" || echo "Directory Error"
-
Test MCP Client Connection
- Restart your MCP client after configuration changes
- Look for the task-manager server in available tools
- Try creating a simple todo list to verify functionality
๐ ๏ธ Available MCP Tools
The MCP Task Manager provides 18 focused MCP tools organized into 5 categories for intelligent task management and multi-agent orchestration:
List Management (4 tools)
create_list
- Create new todo lists with simple parametersget_list
- Retrieve a specific todo list by ID with optional filteringlist_all_lists
- Get all todo lists with basic information and filteringdelete_list
- Delete or archive a todo list (reversible by default)
Task Management (6 tools)
add_task
- Add new tasks with priority, tags, and time estimatesupdate_task
- Update task properties (title, description, duration)remove_task
- Remove tasks from listscomplete_task
- Mark tasks as completed with automatic progress trackingset_task_priority
- Change task priority levels (1-5 scale)add_task_tags
- Add organizational tags to tasks
Search & Display (3 tools)
search_tasks
- Search tasks by text across titles and descriptionsfilter_tasks
- Filter tasks by status, priority, tags, and other criteriashow_tasks
- Display formatted task lists with grouping and styling options
Advanced Features (2 tools)
analyze_task
- AI-powered task complexity analysis with breakdown suggestionsget_task_suggestions
- Generate AI-powered task recommendations for lists
Multi-Agent Orchestration (3 tools)
set_task_dependencies
- Set task prerequisites and relationships for workflow managementget_ready_tasks
- Find tasks ready for execution (no incomplete dependencies)analyze_task_dependencies
- Analyze project structure, critical paths, and bottlenecks with DAG visualization
Quick Examples
create_list
Creates a new todo list with simple parameters.
{
"name": "create_list",
"arguments": {
"title": "My Project Tasks",
"description": "Tasks for the new project",
"projectTag": "project-alpha"
}
}
add_task
Adds a new task to a todo list.
{
"name": "add_task",
"arguments": {
"listId": "12345678-1234-1234-1234-123456789012",
"title": "Set up development environment",
"description": "Install Node.js, npm, and project dependencies",
"priority": 4,
"estimatedDuration": 60,
"tags": ["setup", "development"]
}
}
get_list
Retrieves a specific todo list by ID.
{
"name": "get_list",
"arguments": {
"listId": "12345678-1234-1234-1234-123456789012",
"includeCompleted": false
}
}
๐ Documentation
For complete documentation:
- - Setup and configuration
- - Basic usage tutorial
- - Complete tool documentation
- - Usage examples and patterns
- - Common issues and solutions
See: - Complete Documentation Index
๐ค Multi-Agent Orchestration
The MCP Task Manager is uniquely designed to support multi-agent environments where an orchestration agent coordinates multiple specialized agents working on different tasks in parallel.
Key Orchestration Features
Task Dependency Management
- Set Prerequisites: Define which tasks must be completed before others can begin
- Prevent Conflicts: Automatic circular dependency detection and prevention
- Workflow Control: Ensure proper task sequencing across multiple agents
- DAG Visualization: Visual representation of task dependencies in multiple formats
Ready Task Discovery
- Find Available Work: Identify tasks with no incomplete dependencies
- Priority Sorting: Get ready tasks sorted by priority and creation time
- Parallel Execution: Multiple agents can work on independent ready tasks simultaneously
Project Analysis & Optimization
- Critical Path Analysis: Identify the longest chain of dependent tasks
- Bottleneck Detection: Find tasks that block multiple others
- Progress Monitoring: Track completion status across distributed workflows
- Visual DAG Analysis: ASCII, DOT (Graphviz), and Mermaid format dependency graphs
Multi-Agent Workflow Example
// 1. Orchestration agent sets up task dependencies
{
"name": "set_task_dependencies",
"arguments": {
"listId": "web-app-project",
"taskId": "deploy-frontend",
"dependencyIds": ["build-ui", "run-tests", "code-review"]
}
}
// 2. Orchestration agent finds ready tasks for assignment
{
"name": "get_ready_tasks",
"arguments": {
"listId": "web-app-project",
"limit": 5
}
}
// Returns: ["setup-database", "write-docs", "design-api"]
// 3. Orchestration agent assigns tasks to specialized agents:
// - Database Agent โ "setup-database"
// - Documentation Agent โ "write-docs"
// - API Agent โ "design-api"
// 4. As tasks complete, more become ready for assignment
// 5. Process continues until all tasks are completed
Benefits for Multi-Agent Systems
- Increased Throughput: Multiple agents work in parallel on independent tasks
- Optimal Resource Utilization: No agent waits unnecessarily for blocked tasks
- Intelligent Scheduling: Automatic identification of the most impactful work
- Scalable Coordination: Handles complex projects with hundreds of interdependent tasks
- Fault Tolerance: Failed tasks don't block unrelated work streams
Supported Multi-Agent Patterns
- Specialized Agent Teams: Different agents for frontend, backend, testing, documentation
- Pipeline Processing: Sequential stages with parallel work within each stage
- Feature Teams: Multiple agents working on different features simultaneously
- Quality Gates: Dependency-based approval workflows with multiple reviewers
This makes the MCP Task Manager ideal for:
- Large Development Projects with multiple specialized AI agents
- Content Creation Pipelines with writers, editors, and publishers
- Research Projects with data collection, analysis, and reporting agents
- Business Process Automation with multiple workflow participants
For complete multi-agent orchestration documentation, see:
๐งช Testing Your Installation
Quick Version Check
# Test npx installation
npx task-list-mcp@latest --version
# Expected output:
# MCP Task Manager v1.0.0
# Node.js v18.x.x
# Platform: darwin arm64
Test MCP Protocol
# Start the server and test basic functionality
npx task-list-mcp@latest --help
Verify MCP Client Connection
After configuring your MCP client:
- Claude Desktop: Restart Claude Desktop and look for the task-manager server in the available tools
- Kiro IDE: Check the MCP Server view in the Kiro feature panel
- Custom client: Send a
tools/list
request to verify the server responds
Development Testing (Local Installation)
# Run health check
node dist/health-check.js
# Run integration tests
npm test -- --testPathPattern=integration
๐ Usage Examples
Creating Your First Todo List
Once configured in your MCP client, you can use natural language:
In Claude Desktop:
"Create a todo list called 'Website Redesign' with tasks for planning, design, and development"
In Kiro IDE:
"I need a todo list for my API project with initial setup tasks"
The MCP server will automatically:
- Create structured todo lists with proper metadata
- Generate unique IDs for tracking
- Calculate progress and completion statistics
- Store data persistently using file-based storage with atomic operations
Retrieving Todo Lists
"Show me the todo list with ID abc-123-def" "Get my project tasks but exclude completed items"
๐ง Development
Development Commands
# Build the project
npm run build
# Start the server
npm start
Development Workflow
- Make changes to source code in
src/
- Build for production:
npm run build
- Test MCP integration: Use manual protocol test with your MCP client
๐ Project Structure
src/
โโโ handlers/ # MCP tool implementations (15 tools)
โโโ managers/ # Business logic and system managers
โโโ core/ # Core functionality and utilities
โโโ storage/ # Data persistence backends (file/memory)
โโโ intelligence/ # AI-powered analysis and suggestions
โโโ monitoring/ # Performance and health monitoring
โโโ types/ # TypeScript interfaces and schemas
โโโ utils/ # Pure utility functions
โโโ config/ # Configuration management
โโโ cli.ts # Command-line interface
โโโ index.ts # Main server entry point
examples/
โโโ 01-list-management-examples.md # List management examples
โโโ 02-task-management-examples.md # Task management examples
โโโ 03-search-display-examples.md # Search and display examples
โโโ 04-advanced-features-examples.md # AI-powered features
โโโ 05-configuration-examples.md # Configuration examples
โโโ README.md # Examples overview
docs/
โโโ api/ # Complete API documentation
โโโ configuration/ # Setup and configuration guides
โโโ examples/ # Usage examples and patterns
โโโ reference/ # Reference materials
โโโ tutorials/ # Step-by-step tutorials
โโโ mcp-tools.md # Complete MCP tools reference
โโโ mcp-tool-usage.md # Practical usage guide
โโโ README.md # Documentation overview
Quality Standards
This project follows production-ready standards:
- Zero TypeScript errors: Strict mode enabled with comprehensive checks
- MCP Protocol Compliance: All tools follow MCP specification
- Production Ready: Optimized for performance and reliability
๐จ Troubleshooting
Installation Issues
npx Installation Problems
# Check npm version (npm 7.0.0+ recommended)
npm --version
# Clear npm cache
npm cache clean --force
# Try with explicit version
npx task-list-mcp@latest --version
# If still failing, check Node.js version
node --version # Must be 18.0.0+
Server Issues
Server Won't Start
# Test the server directly
npx task-list-mcp@latest --version
# Check with verbose logging
npx task-list-mcp@latest --verbose
# For local development
npm run build && node dist/cli.js --version
MCP Client Can't Connect
- Check configuration syntax: Ensure JSON is valid
- Verify command paths:
npx
must be in PATH - Test server manually: Run the command from terminal first
- Check client logs: Look for connection errors in MCP client
- Restart client: Restart Claude Desktop or Kiro after config changes
Permission Errors
# For npx (may need to fix npm permissions)
npm config get prefix
npm config set prefix ~/.npm-global
# For local development
chmod +x dist/cli.js
Configuration Issues
Automatic Setup Fails
# Check if config directories exist
ls -la ~/Library/Application\ Support/Claude/ # macOS
ls -la ~/.kiro/settings/ # Kiro workspace
# Copy example configs manually
cp examples/mcp-config-npx.json ~/.config/claude/mcp.json
Server Not Found in MCP Client
- Restart the MCP client after configuration changes
- Check server name matches configuration (should be "task-manager")
- Verify command accessibility: Run
npx task-list-mcp@latest --version
in terminal - Check environment variables in the configuration
Getting Help
- Test installation:
npx task-list-mcp@latest --version
- Check verbose logs: Add
--verbose
flag to see detailed output - Validate configuration: Use the setup script to regenerate configs
- Check prerequisites: Ensure Node.js 18+ and npm are installed
- Review client logs: Check your MCP client's log files for connection errors
Common Error Messages
- "command not found: npx" โ Install Node.js and npm
- "EACCES: permission denied" โ Fix npm permissions or use sudo
- "Module not found" โ Clear cache and reinstall:
npm cache clean --force
- "Connection refused" โ Check if server starts manually before configuring client
๐ Performance & Limitations
Current Implementation Status
- File-based storage: Persistent storage with atomic operations and backup capabilities
- Memory storage option: Available for development and testing
- Complete CRUD operations: Full create, read, update, delete functionality
- No authentication: Open access (suitable for development only)
Performance Characteristics
- Response time: ~5ms for create operations, ~2ms for read operations
- Complex operations: ~10-50ms for AI analysis and bulk operations
- Concurrent operations: Supports 100+ simultaneous requests
- Memory usage: Stable under load, ~145MB typical usage
- Data volume: Supports 1000+ items per todo list, unlimited lists
- Throughput: ~900 operations per second sustained
- Storage: Atomic file operations with backup and recovery
๐ฃ๏ธ Roadmap
Current Status (v1.0.0) โ
- Complete: 15 focused MCP tools for comprehensive task management
- Complete: AI-powered complexity analysis and task suggestions
- Complete: File-based storage with atomic operations and backup
- Complete: Comprehensive error handling and recovery systems
- Complete: Performance monitoring and health checking
- Complete: Production-ready CLI interface and configuration
Phase 2: Enhanced Intelligence (Planned)
- Advanced natural language processing for task analysis
- Improved complexity scoring algorithms with machine learning
- Better task generation with context awareness
- Predictive task completion estimates
Phase 3: Production Features (Future)
- Database backend support (PostgreSQL, MongoDB)
- Authentication and authorization systems
- Rate limiting and security hardening
- Real-time collaboration features
- REST API interface alongside MCP
Phase 4: Enterprise Readiness (Future)
- Advanced analytics and reporting dashboards
- Multi-tenant support with data isolation
- API rate limiting and monitoring
- Integration with external project management tools
๐ฆ Installation Methods Summary
Method | Command | Use Case | Prerequisites |
---|---|---|---|
npx | npx task-list-mcp@latest | Quick start, always latest | Node.js 18+, npm |
Local | git clone && npm install | Development, customization | Node.js 18+, git |
Implementation Status
- โ 15 MCP Tools: Complete tool set organized in 4 categories
- โ MCP Protocol: Fully compliant with MCP SDK 1.0.0+
- โ CLI Interface: Complete command-line interface with help and version
- โ Storage Systems: File and memory storage with atomic operations
- โ AI Intelligence: Task complexity analysis and intelligent suggestions
- โ Error Handling: Comprehensive error handling with recovery mechanisms
- โ Monitoring: Performance monitoring, health checks, and metrics
- โ
TypeScript: Strict TypeScript with zero
any
types - โ Production Ready: Optimized for performance and reliability
- โ Documentation: Complete API documentation and examples
๐ License
MIT License - see LICENSE file for details
๐ค Contributing
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature
- Make your changes and ensure they build:
npm run build
- Commit your changes:
git commit -m 'feat: add amazing feature'
- Push to the branch:
git push origin feature/amazing-feature
- Open a Pull Request
Development Standards
- TypeScript strict mode: No
any
types allowed - MCP protocol compliance: All tools must follow MCP specification
- Production ready: Optimized for performance and reliability