# User Guide - Task Manager MCP Servers ## Getting Started ### Prerequisites - Python 3.9 or higher - OpenAI API key (for AI features) - Claude Desktop (for MCP integration) ### Installation 1. **Install the package:** ```bash pip install task-manager-mcp ``` 2. **Set up environment variables:** ```bash export OPENAI_API_KEY="your-openai-api-key" export OPENAI_BASE_URL="https://api.openai.com/v1" # Optional ``` 3. **Configure Claude Desktop:** Edit your Claude Desktop configuration file: - **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json` - **Windows**: `%APPDATA%\Claude\claude_desktop_config.json` ```json { "mcpServers": { "task-management": { "command": "python", "args": ["-m", "task_management_mcp.server"], "env": { "OPENAI_API_KEY": "your-openai-api-key" } }, "task-assignment": { "command": "python", "args": ["-m", "task_assignment_mcp.server"], "env": { "OPENAI_API_KEY": "your-openai-api-key" } } } } ``` 4. **Restart Claude Desktop** to load the MCP servers. ## Basic Usage ### Task Management Workflows #### 1. Creating and Analyzing Tasks Start by describing your task in natural language: ``` "I need to build a user authentication system for my web app. It should include login, registration, password reset, and email verification features. The deadline is in 2 weeks." ``` The system will: - Extract structured task information - Estimate time and complexity - Assign priority levels - Identify potential risks #### 2. Getting Schedule Recommendations Ask for scheduling help: ``` "Can you recommend the best order to work on these tasks? I have 6 hours available per day." ``` You'll get: - Optimal task ordering - Estimated completion dates - Critical path analysis - Parallel execution opportunities #### 3. Risk Assessment and Mitigation For any task, you can ask: ``` "What are the potential risks for the authentication system task, and how can I mitigate them?" ``` The system provides: - Risk level assessment (1-5 scale) - Specific risk factors - Actionable mitigation strategies - Early warning indicators #### 4. Progress Tracking Update progress as you work: ``` "I've completed 30% of the authentication task and spent 3 hours on it. The login functionality is working." ``` The system will: - Update task progress - Adjust time estimates - Recalculate schedules - Suggest next steps #### 5. Smart Task Recommendations When you're ready for the next task: ``` "I have 2 hours available. What should I work on next?" ``` Get personalized recommendations based on: - Available time - Task priorities - Dependencies - Your current context ### Task Assignment Workflows #### 1. Task Decomposition For complex tasks, ask for breakdown: ``` "This e-commerce platform task seems too big. Can you break it down into smaller, manageable pieces?" ``` The system will: - Analyze task complexity - Create logical subtasks - Estimate time for each piece - Maintain dependencies #### 2. Resource Matching and Assignment When you have team members: ``` "I have a React component task. Who should I assign it to based on skills and availability?" ``` Get recommendations considering: - Skill matching - Current workload - Cost efficiency - Past performance #### 3. Team Collaboration Planning For multi-person tasks: ``` "This full-stack feature needs both frontend and backend work. How should the team collaborate?" ``` Receive detailed plans including: - Team composition - Coordination strategy - Communication plan - Milestone schedule #### 4. Daily Report Review Team members can submit daily reports: ``` "Today I completed the user profile API, wrote comprehensive tests, and helped review the frontend integration. I also optimized the database queries for better performance." ``` Get automated feedback with: - Performance scoring (productivity, quality, collaboration) - Specific achievements recognition - Areas for improvement - Constructive suggestions ## Advanced Features ### Custom Resource Management Define your team members and AI agents: ```json { "human_resources": [ { "id": "dev_001", "name": "Sarah Chen", "skills": ["react", "typescript", "ui_design"], "cost_per_hour": 85.0, "availability": "full_time" } ], "ai_agents": [ { "id": "code_agent", "name": "Code Generation Agent", "skills": ["code_generation", "testing", "documentation"], "cost_per_task": 0.5 } ] } ``` ### Project-Level Management Organize tasks by projects: ``` "Create a new project called 'Mobile App' and analyze these requirements: [requirements document]" ``` Track progress across entire projects: ``` "Show me the overall status of the Mobile App project" ``` ### Integration with Development Tools The MCP servers can integrate with: - **Git repositories**: Track commits and relate to tasks - **Issue trackers**: Sync with GitHub Issues, Jira - **Time tracking**: Export time logs - **Calendar apps**: Schedule task work ## Best Practices ### Task Description Guidelines **Good task descriptions:** - Be specific about deliverables - Include acceptance criteria - Mention technical constraints - Specify deadlines if known **Example:** ``` "Implement user authentication API with JWT tokens. Must include login, logout, token refresh, and password reset endpoints. Use FastAPI and PostgreSQL. Should handle rate limiting and include comprehensive tests. Deadline: March 15th." ``` ### Effective Progress Updates **Include in progress updates:** - Specific accomplishments - Time spent - Challenges encountered - Next steps planned **Example:** ``` "Completed login and logout endpoints (40% progress, 3 hours spent). Encountered issue with JWT token expiration handling - researching best practices. Next: implement token refresh endpoint." ``` ### Team Collaboration Tips 1. **Regular Check-ins**: Use daily report reviews 2. **Clear Dependencies**: Identify task dependencies early 3. **Skill Development**: Track team member growth 4. **Workload Balance**: Monitor resource utilization ## Troubleshooting ### Common Issues #### MCP Server Not Starting - Check Python version (3.9+ required) - Verify environment variables are set - Check Claude Desktop configuration syntax #### AI Features Not Working - Verify OpenAI API key is valid - Check API quota and billing - Ensure network connectivity #### Poor Task Recommendations - Provide more detailed task descriptions - Update resource skills and availability - Review and adjust task priorities ### Getting Help 1. **Check logs**: Look for error messages in Claude Desktop 2. **Validate configuration**: Use the provided examples 3. **Test with demo script**: Run `python examples/demo.py` 4. **Community support**: GitHub Discussions and Issues ## Tips for Maximum Productivity ### Daily Workflow 1. **Morning Planning**: Get task recommendations for the day 2. **Regular Updates**: Update progress every few hours 3. **End-of-Day Review**: Reflect on completed tasks 4. **Weekly Planning**: Review project status and adjust priorities ### Team Management 1. **Skill Tracking**: Keep resource skills updated 2. **Performance Monitoring**: Review daily reports regularly 3. **Workload Balancing**: Monitor team capacity 4. **Continuous Improvement**: Use retrospective insights ### Project Success 1. **Clear Requirements**: Start with detailed task analysis 2. **Risk Management**: Address risks proactively 3. **Regular Reviews**: Track progress against schedules 4. **Adaptive Planning**: Adjust plans based on actual progress ## Next Steps Once you're comfortable with basic usage: 1. **Explore Advanced Features**: Custom resources, project management 2. **Integrate with Tools**: Connect to your development workflow 3. **Customize Workflows**: Adapt to your team's processes 4. **Share Feedback**: Help improve the system with your insights For detailed API reference, see [API_REFERENCE.md](API_REFERENCE.md).