Taskmaster

Instructions

Implementation Reference

• mcp-server/src/core/direct-functions/models.js:60-129 (handler)

  Primary handler function `modelsDirect` implementing core logic: handles model listing, setting for roles (main/research/fallback), configuration retrieval, and validation.
  export async function modelsDirect(args, log, context = {}) { const { session } = context; const { projectRoot } = args; // Extract projectRoot from args // Create a logger wrapper that the core functions can use const mcpLog = createLogWrapper(log); log.info(`Executing models_direct with args: ${JSON.stringify(args)}`); log.info(`Using project root: ${projectRoot}`); // Validate flags: only one custom provider flag can be used simultaneously const customProviderFlags = CUSTOM_PROVIDERS_ARRAY.filter( (provider) => args[provider] ); if (customProviderFlags.length > 1) { log.error( 'Error: Cannot use multiple custom provider flags simultaneously.' ); return { success: false, error: { code: 'INVALID_ARGS', message: 'Cannot use multiple custom provider flags simultaneously. Choose only one: openrouter, ollama, bedrock, azure, vertex, or openai-compatible.' } }; } try { enableSilentMode(); try { // Check for the listAvailableModels flag if (args.listAvailableModels === true) { return await getAvailableModelsList({ session, mcpLog, projectRoot }); } // Handle setting any model role using unified function const modelContext = { session, mcpLog, projectRoot }; const modelSetResult = await handleModelSetting(args, modelContext); if (modelSetResult) { return modelSetResult; } // Default action: get current configuration return await getModelConfiguration({ session, mcpLog, projectRoot }); } finally { disableSilentMode(); } } catch (error) { log.error(`Error in models_direct: ${error.message}`); return { success: false, error: { code: 'DIRECT_FUNCTION_ERROR', message: error.message, details: error.stack } }; } }
• mcp-server/src/tools/models.js:19-81 (schema)

  Zod input schema for the 'models' tool parameters, defining options for setting main/research/fallback models, listing available models, and provider flags.
  parameters: z.object({ setMain: z .string() .optional() .describe( 'Set the primary model for task generation/updates. Model provider API key is required in the MCP config ENV.' ), setResearch: z .string() .optional() .describe( 'Set the model for research-backed operations. Model provider API key is required in the MCP config ENV.' ), setFallback: z .string() .optional() .describe( 'Set the model to use if the primary fails. Model provider API key is required in the MCP config ENV.' ), listAvailableModels: z .boolean() .optional() .describe( 'List all available models not currently in use. Input/output costs values are in dollars (3 is $3.00).' ), projectRoot: z .string() .describe('The directory of the project. Must be an absolute path.'), openrouter: z .boolean() .optional() .describe('Indicates the set model ID is a custom OpenRouter model.'), ollama: z .boolean() .optional() .describe('Indicates the set model ID is a custom Ollama model.'), bedrock: z .boolean() .optional() .describe('Indicates the set model ID is a custom AWS Bedrock model.'), azure: z .boolean() .optional() .describe('Indicates the set model ID is a custom Azure OpenAI model.'), vertex: z .boolean() .optional() .describe( 'Indicates the set model ID is a custom Google Vertex AI model.' ), 'openai-compatible': z .boolean() .optional() .describe( 'Indicates the set model ID is a custom OpenAI-compatible model. Requires baseURL parameter.' ), baseURL: z .string() .optional() .describe( 'Custom base URL for providers that support it (e.g., https://api.example.com/v1).' ) }),
• mcp-server/src/tools/models.js:14-107 (registration)

  `registerModelsTool` function that adds the 'models' MCP tool to the server with name, description, schema, and thin wrapper execute handler calling `modelsDirect`.
  export function registerModelsTool(server) { server.addTool({ name: 'models', description: 'Get information about available AI models or set model configurations. Run without arguments to get the current model configuration and API key status for the selected model providers.', parameters: z.object({ setMain: z .string() .optional() .describe( 'Set the primary model for task generation/updates. Model provider API key is required in the MCP config ENV.' ), setResearch: z .string() .optional() .describe( 'Set the model for research-backed operations. Model provider API key is required in the MCP config ENV.' ), setFallback: z .string() .optional() .describe( 'Set the model to use if the primary fails. Model provider API key is required in the MCP config ENV.' ), listAvailableModels: z .boolean() .optional() .describe( 'List all available models not currently in use. Input/output costs values are in dollars (3 is $3.00).' ), projectRoot: z .string() .describe('The directory of the project. Must be an absolute path.'), openrouter: z .boolean() .optional() .describe('Indicates the set model ID is a custom OpenRouter model.'), ollama: z .boolean() .optional() .describe('Indicates the set model ID is a custom Ollama model.'), bedrock: z .boolean() .optional() .describe('Indicates the set model ID is a custom AWS Bedrock model.'), azure: z .boolean() .optional() .describe('Indicates the set model ID is a custom Azure OpenAI model.'), vertex: z .boolean() .optional() .describe( 'Indicates the set model ID is a custom Google Vertex AI model.' ), 'openai-compatible': z .boolean() .optional() .describe( 'Indicates the set model ID is a custom OpenAI-compatible model. Requires baseURL parameter.' ), baseURL: z .string() .optional() .describe( 'Custom base URL for providers that support it (e.g., https://api.example.com/v1).' ) }), execute: withToolContext('models', async (args, context) => { try { context.log.info( `Starting models tool with args: ${JSON.stringify(args)}` ); // Use args.projectRoot directly (normalized by withToolContext) const result = await modelsDirect( { ...args, projectRoot: args.projectRoot }, context.log, { session: context.session } ); return handleApiResult({ result, log: context.log, errorPrefix: 'Error managing models', projectRoot: args.projectRoot }); } catch (error) { context.log.error(`Error in models tool: ${error.message}`); return createErrorResponse(error.message); } }) }); }
• mcp-server/src/tools/tool-registry.js:59-104 (registration)

  Central tool registry object mapping tool name 'models' to `registerModelsTool` for dynamic server registration.
  export const toolRegistry = { initialize_project: registerInitializeProjectTool, models: registerModelsTool, rules: registerRulesTool, parse_prd: registerParsePRDTool, 'response-language': registerResponseLanguageTool, analyze_project_complexity: registerAnalyzeProjectComplexityTool, expand_task: registerExpandTaskTool, expand_all: registerExpandAllTool, scope_up_task: registerScopeUpTool, scope_down_task: registerScopeDownTool, get_tasks: registerGetTasksTool, get_task: registerGetTaskTool, next_task: registerNextTaskTool, complexity_report: registerComplexityReportTool, set_task_status: registerSetTaskStatusTool, add_task: registerAddTaskTool, add_subtask: registerAddSubtaskTool, update: registerUpdateTool, update_task: registerUpdateTaskTool, update_subtask: registerUpdateSubtaskTool, remove_task: registerRemoveTaskTool, remove_subtask: registerRemoveSubtaskTool, clear_subtasks: registerClearSubtasksTool, move_task: registerMoveTaskTool, add_dependency: registerAddDependencyTool, remove_dependency: registerRemoveDependencyTool, validate_dependencies: registerValidateDependenciesTool, fix_dependencies: registerFixDependenciesTool, list_tags: registerListTagsTool, add_tag: registerAddTagTool, delete_tag: registerDeleteTagTool, use_tag: registerUseTagTool, rename_tag: registerRenameTagTool, copy_tag: registerCopyTagTool, research: registerResearchTool, autopilot_start: registerAutopilotStartTool, autopilot_resume: registerAutopilotResumeTool, autopilot_next: registerAutopilotNextTool, autopilot_status: registerAutopilotStatusTool, autopilot_complete: registerAutopilotCompleteTool, autopilot_commit: registerAutopilotCommitTool, autopilot_finalize: registerAutopilotFinalizeTool, autopilot_abort: registerAutopilotAbortTool, generate: registerGenerateTool };
• scripts/modules/task-manager/models.js:148-272 (helper)

  Helper `getModelConfiguration` used by handler to fetch and format current model configs, API key statuses, and model details for main/research/fallback roles.
  async function getModelConfiguration(options = {}) { const { mcpLog, projectRoot, session } = options; const report = (level, ...args) => { if (mcpLog && typeof mcpLog[level] === 'function') { mcpLog[level](...args); } }; if (!projectRoot) { throw new Error('Project root is required but not found.'); } // Use centralized config path finding instead of hardcoded path const configPath = findConfigPath(null, { projectRoot }); const configExists = isConfigFilePresent(projectRoot); log( 'debug', `Checking for config file using findConfigPath, found: ${configPath}` ); log( 'debug', `Checking config file using isConfigFilePresent(), exists: ${configExists}` ); if (!configExists) { throw new Error(CONFIG_MISSING_ERROR); } try { // Get current settings - these should use the config from the found path automatically const mainProvider = getMainProvider(projectRoot); const mainModelId = getMainModelId(projectRoot); const mainBaseURL = getBaseUrlForRole('main', projectRoot); const researchProvider = getResearchProvider(projectRoot); const researchModelId = getResearchModelId(projectRoot); const researchBaseURL = getBaseUrlForRole('research', projectRoot); const fallbackProvider = getFallbackProvider(projectRoot); const fallbackModelId = getFallbackModelId(projectRoot); const fallbackBaseURL = getBaseUrlForRole('fallback', projectRoot); // Check API keys const mainCliKeyOk = isApiKeySet(mainProvider, session, projectRoot); const mainMcpKeyOk = getMcpApiKeyStatus(mainProvider, projectRoot); const researchCliKeyOk = isApiKeySet( researchProvider, session, projectRoot ); const researchMcpKeyOk = getMcpApiKeyStatus(researchProvider, projectRoot); const fallbackCliKeyOk = fallbackProvider ? isApiKeySet(fallbackProvider, session, projectRoot) : true; const fallbackMcpKeyOk = fallbackProvider ? getMcpApiKeyStatus(fallbackProvider, projectRoot) : true; // Get available models to find detailed info const availableModels = getAvailableModels(projectRoot); // Find model details const mainModelData = availableModels.find((m) => m.id === mainModelId); const researchModelData = availableModels.find( (m) => m.id === researchModelId ); const fallbackModelData = fallbackModelId ? availableModels.find((m) => m.id === fallbackModelId) : null; // Return structured configuration data return { success: true, data: { activeModels: { main: { provider: mainProvider, modelId: mainModelId, baseURL: mainBaseURL, sweScore: mainModelData?.swe_score || null, cost: mainModelData?.cost_per_1m_tokens || null, keyStatus: { cli: mainCliKeyOk, mcp: mainMcpKeyOk } }, research: { provider: researchProvider, modelId: researchModelId, baseURL: researchBaseURL, sweScore: researchModelData?.swe_score || null, cost: researchModelData?.cost_per_1m_tokens || null, keyStatus: { cli: researchCliKeyOk, mcp: researchMcpKeyOk } }, fallback: fallbackProvider ? { provider: fallbackProvider, modelId: fallbackModelId, baseURL: fallbackBaseURL, sweScore: fallbackModelData?.swe_score || null, cost: fallbackModelData?.cost_per_1m_tokens || null, keyStatus: { cli: fallbackCliKeyOk, mcp: fallbackMcpKeyOk } } : null }, message: 'Successfully retrieved current model configuration' } }; } catch (error) { report('error', `Error getting model configuration: ${error.message}`); return { success: false, error: { code: 'CONFIG_ERROR', message: error.message } }; } }