99 lines
2.7 KiB
JavaScript
99 lines
2.7 KiB
JavaScript
/**
|
|
* models.js
|
|
* MCP tool for managing AI model configurations
|
|
*/
|
|
|
|
import { z } from 'zod';
|
|
import {
|
|
handleApiResult,
|
|
createErrorResponse,
|
|
withNormalizedProjectRoot
|
|
} from './utils.js';
|
|
import { modelsDirect } from '../core/task-master-core.js';
|
|
|
|
/**
|
|
* Register the models tool with the MCP server
|
|
* @param {Object} server - FastMCP server instance
|
|
*/
|
|
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.'
|
|
)
|
|
}),
|
|
execute: withNormalizedProjectRoot(async (args, { log, session }) => {
|
|
try {
|
|
log.info(`Starting models tool with args: ${JSON.stringify(args)}`);
|
|
|
|
// Use args.projectRoot directly (guaranteed by withNormalizedProjectRoot)
|
|
const result = await modelsDirect(
|
|
{ ...args, projectRoot: args.projectRoot },
|
|
log,
|
|
{ session }
|
|
);
|
|
|
|
return handleApiResult(
|
|
result,
|
|
log,
|
|
'Error managing models',
|
|
undefined,
|
|
args.projectRoot
|
|
);
|
|
} catch (error) {
|
|
log.error(`Error in models tool: ${error.message}`);
|
|
return createErrorResponse(error.message);
|
|
}
|
|
})
|
|
});
|
|
}
|