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

.cursor/rules/dev_workflow.mdc

@@ -107,8 +107,8 @@ Taskmaster configuration is managed through two main mechanisms:
     *   Located in the project root directory.
     *   Stores most configuration settings: AI model selections (main, research, fallback), parameters (max tokens, temperature), logging level, default subtasks/priority, project name, etc.
     *   **Managed via `task-master models --setup` command.** Do not edit manually unless you know what you are doing.
+    *   **View/Set specific models via `task-master models` command or `models` MCP tool.**
     *   Created automatically when you run `task-master models --setup` for the first time.
-    *   View the current configuration using `task-master models`.
 
 2.  **Environment Variables (`.env` / `mcp.json`):**
     *   Used **only** for sensitive API keys and specific endpoint URLs.
@@ -116,7 +116,7 @@ Taskmaster configuration is managed through two main mechanisms:
     *   For MCP/Cursor integration, configure these keys in the `env` section of `.cursor/mcp.json`.
     *   Available keys/variables: See `assets/env.example` or the `Configuration` section in [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc).
 
-**Important:** Non-API key settings (like `MODEL`, `MAX_TOKENS`, `LOG_LEVEL`) are **no longer configured via environment variables**. Use `task-master models --setup` instead.
+**Important:** Non-API key settings (like model selections, `MAX_TOKENS`, `LOG_LEVEL`) are **no longer configured via environment variables**. Use the `task-master models` command (or `--setup` for interactive configuration) or the `models` MCP tool.
 **If AI commands FAIL in MCP** verify that the API key for the selected provider is present in the mcp.json
 **If AI commands FAIL in CLI** verify that the API key for the selected provider is present in the .env in the root of the project.
 
@@ -215,5 +215,10 @@ Once a task has been broken down into subtasks using `expand_task` or similar me
       `rg "export (async function|function|const) \w+"` or similar patterns.
     - Can help compare functions between files during migrations or identify potential naming conflicts.
 
+---
+*This workflow provides a general guideline. Adapt it based on your specific project needs and team practices.*
+      `rg "export (async function|function|const) \w+"` or similar patterns.
+    - Can help compare functions between files during migrations or identify potential naming conflicts.
+
 ---
 *This workflow provides a general guideline. Adapt it based on your specific project needs and team practices.*

.cursor/rules/taskmaster.mdc

@@ -55,6 +55,31 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 
 ---
 
+## AI Model Configuration
+
+### 2. Manage Models (`models`)
+*   **MCP Tool:** `models`
+*   **CLI Command:** `task-master models [options]`
+*   **Description:** `View the current AI model configuration or set specific models for different roles (main, research, fallback).`
+*   **Key MCP Parameters/Options:**
+    *   `setMain <model_id>`: `Set the primary model ID for task generation/updates.` (CLI: `--set-main <model_id>`)
+    *   `setResearch <model_id>`: `Set the model ID for research-backed operations.` (CLI: `--set-research <model_id>`)
+    *   `setFallback <model_id>`: `Set the model ID to use if the primary fails.` (CLI: `--set-fallback <model_id>`)
+    *   `listAvailableModels <boolean>`: `If true, lists available models not currently assigned to a role.` (CLI: No direct equivalent; CLI lists available automatically)
+    *   `projectRoot <string>`: `Optional. Absolute path to the project root directory.` (CLI: Determined automatically)
+*   **Key CLI Options:**
+    *   `--set-main <model_id>`: `Set the primary model.`
+    *   `--set-research <model_id>`: `Set the research model.`
+    *   `--set-fallback <model_id>`: `Set the fallback model.`
+    *   `--setup`: `Run interactive setup to configure models and other settings.`
+*   **Usage (MCP):** Call without set flags to get current config. Use `setMain`, `setResearch`, or `setFallback` with a valid model ID to update the configuration. Use `listAvailableModels: true` to get a list of unassigned models.
+*   **Usage (CLI):** Run without flags to view current configuration and available models. Use set flags to update specific roles. Use `--setup` for guided configuration.
+*   **Notes:** Configuration is stored in `.taskmasterconfig` in the project root. This command/tool modifies that file. Use `listAvailableModels` to ensure the selected model is supported. 
+*   **API note:** API keys for selected AI providers (based on their model) need to exist in the mcp.json file to be accessible in MCP context. The API keys must be present in the local .env file for the CLI to be able to read them.
+*   **Warning:** DO NOT MANUALLY EDIT THE .taskmasterconfig FILE. Use the included commands either in the MCP or CLI format as needed. Always prioritize MCP tools when available and use the CLI as a fallback.
+
+---
+
 ## Task Listing & Viewing
 
 ### 3. Get Tasks (`get_tasks`)