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eat(models): Add MCP support for models command and improve configuration docs

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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
This commit is contained in:
Eyal Toledano
2025-04-23 15:47:33 -04:00
parent 78a5376796
commit 6cb213ebbd
13 changed files with 1291 additions and 565 deletions
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9
.cursor/rules/dev_workflow.mdc
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@@ -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.*