- Fix provider configuration from 'openai' to 'ollama' in .taskmaster/config.json
- Remove conflicting MCP configurations (.cursor/mcp.json, packages/.cursor/mcp.json)
- Standardize on single .vscode/mcp.json configuration for VS Code
- Update environment variables for proper Ollama integration
- Add .env.taskmaster for easy environment setup
- Verify AI functionality: task creation, expansion, and research working
- All models (qwen2.5-coder:7b, deepseek-r1:7b, llama3.1:8b) operational
- Cost: /run/current-system/sw/bin/zsh (using local Ollama server at grey-area:11434)
Resolves configuration conflicts and enables full AI-powered task management
with local models instead of external API dependencies.
- Updated .cursor/mcp.json to use local Nix-built Task Master binary
- Configured Task Master to use local Ollama models via OpenAI-compatible API
- Set up three models: qwen3:4b (main), deepseek-r1:1.5b (research), gemma3:4b-it-qat (fallback)
- Created comprehensive integration status documentation
- Task Master successfully running as MCP server with 23+ available tools
- Ready for VS Code/Cursor AI chat integration
