a9f490882a
- Added detailed status report covering completed work - Documented current configuration for Ollama integration - Listed all available MCP tools and their functionality - Included troubleshooting guide and next steps - Documented architecture and workflow for VS Code MCP integration
122 lines
4.3 KiB
Markdown
122 lines
4.3 KiB
Markdown
# Claude Task Master AI - Nix Package & VS Code MCP Integration
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## Current Status
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### ✅ Completed
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1. **Nix Package**: Successfully built and packaged Claude Task Master AI
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2. **Local Installation**: Binary available at `/home/geir/Home-lab/result/bin/task-master-ai`
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3. **Ollama Integration**: Configured to use local Ollama models on grey-area:11434
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4. **VS Code MCP Setup**: Configured for integration with Cursor/VS Code
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### 🔧 Configuration Files
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#### Task Master Configuration
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- **Location**: `/home/geir/Home-lab/.taskmaster/config.json`
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- **Models**:
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- Main: `qwen3:4b` (general tasks)
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- Research: `deepseek-r1:1.5b` (reasoning tasks)
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- Fallback: `gemma3:4b-it-qat` (backup)
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- **Provider**: `openai` (using OpenAI-compatible API)
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- **Base URL**: `http://grey-area:11434/v1`
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#### VS Code MCP Configuration
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- **Location**: `/home/geir/Home-lab/.cursor/mcp.json`
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- **Command**: Direct path to Nix-built binary
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- **Environment**: OpenAI-compatible mode with local Ollama
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### 🎯 Available MCP Tools
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The Task Master MCP server provides these tools for AI assistants:
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#### Project Management
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- `initialize_project` - Set up new Task Master project
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- `models` - Configure AI models and check status
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- `parse_prd` - Generate tasks from PRD documents
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#### Task Operations
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- `get_tasks` - List all tasks with filtering
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- `get_task` - Get specific task details
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- `next_task` - Find next task to work on
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- `add_task` - Create new tasks with AI
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- `update_task` - Update existing task
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- `set_task_status` - Change task status
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- `remove_task` - Delete tasks
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#### Subtask Management
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- `add_subtask` - Add subtasks to existing tasks
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- `update_subtask` - Update subtask information
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- `remove_subtask` - Remove subtasks
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- `clear_subtasks` - Clear all subtasks from tasks
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#### Advanced Features
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- `expand_task` - Break down tasks into subtasks
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- `expand_all` - Auto-expand all pending tasks
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- `analyze_project_complexity` - Complexity analysis
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- `complexity_report` - View complexity reports
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#### Dependencies
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- `add_dependency` - Create task dependencies
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- `remove_dependency` - Remove dependencies
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- `validate_dependencies` - Check for issues
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- `fix_dependencies` - Auto-fix dependency problems
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### 🚀 Usage in VS Code
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1. **Restart VS Code/Cursor** after updating `.cursor/mcp.json`
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2. **Access via AI Chat**: Use Claude or GitHub Copilot
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3. **Example Commands**:
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- "Initialize a new Task Master project in my current directory"
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- "Create a task for setting up a new home lab service"
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- "Show me the next task I should work on"
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- "Expand task 5 into detailed subtasks"
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### 🔍 Current Issue
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The Task Master binary works as an MCP server but appears to hang when making AI API calls to Ollama. This might be due to:
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1. **Network connectivity** between the host and grey-area
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2. **OpenAI API compatibility** formatting differences
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3. **Authentication** handling with the fake API key
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**Workaround**: Use Task Master through the MCP interface in VS Code, where the AI assistant can handle the tool calls without direct API communication.
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### 🛠️ Troubleshooting
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#### Check Ollama Connectivity
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```bash
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curl -X POST http://grey-area:11434/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{"model": "qwen3:4b", "messages": [{"role": "user", "content": "Hello"}]}'
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```
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#### Verify Task Master Tools
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```bash
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cd /home/geir/Home-lab
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echo '{"jsonrpc": "2.0", "id": 1, "method": "tools/list", "params": {}}' | \
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OPENAI_API_KEY="fake-key" OPENAI_BASE_URL="http://grey-area:11434/v1" \
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./result/bin/task-master-ai
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```
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#### Check MCP Server Status
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In VS Code, open the Output panel and look for MCP server connection logs.
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### 📋 Next Steps
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1. **Test MCP Integration**: Try using Task Master tools through VS Code AI chat
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2. **Debug API Connectivity**: Investigate why Task Master hangs on API calls
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3. **Create Sample Project**: Initialize a test project to validate functionality
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4. **Documentation**: Create user guides for common workflows
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### 🏗️ Architecture
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```
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VS Code/Cursor (AI Chat)
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↓ MCP Protocol
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Task Master AI (Nix Binary)
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↓ OpenAI-compatible API
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Ollama (grey-area:11434)
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↓ Model Inference
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Local Models (qwen3:4b, deepseek-r1:1.5b, gemma3:4b-it-qat)
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```
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This setup provides a complete local AI-powered task management system integrated with your development environment while maintaining full privacy and control over your data.
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