claude-task-master/violet-parrots-march.md at 90c6c1e587ce46cc4c3cb3cc82801a919b85c3af

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Eyal Toledano 6cb213ebbd eat(models): Add MCP support for models command and improve configuration docs

This commit implements several related improvements to the models command and configuration system:

- Added MCP support for the models command:
  - Created new direct function implementation in models.js
  - Registered modelsDirect in task-master-core.js for proper export
  - Added models tool registration in tools/index.js
  - Ensured project name replacement when copying .taskmasterconfig in init.js

- Improved .taskmasterconfig copying during project initialization:
  - Added copyTemplateFile() call in createProjectStructure()
  - Ensured project name is properly replaced in the config

- Restructured tool registration in logical workflow groups:
  - Organized registration into 6 functional categories
  - Improved command ordering to follow typical workflow
  - Added clear group comments for maintainability

- Enhanced documentation in cursor rules:
  - Updated dev_workflow.mdc with clearer config management instructions
  - Added comprehensive models command reference to taskmaster.mdc
  - Clarified CLI vs MCP usage patterns and options
  - Added warning against manual .taskmasterconfig editing

2025-04-23 15:47:33 -04:00

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task-master-ai

task-master-ai
patch

Adds a 'models' CLI and MCP command to get the current model configuration, available models, and gives the ability to set main/research/fallback models."
In the CLI, task-master models shows the current models config. Using the --setup flag launches an interactive set up that allows you to easily select the models you want to use for each of the three roles. Use q during the interactive setup to cancel the setup.
In the MCP, responses are simplified in RESTful format (instead of the full CLI output). The agent can use the models tool with different arguments, including listAvailableModels to get available models. Run without arguments, it will return the current configuration. Arguments are available to set the model for each of the three roles. This allows you to manage Taskmaster AI providers and models directly from either the CLI or MCP or both.
Updated the CLI help menu when you run task-master to include missing commands and .taskmasterconfig information.

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