CC-Meta

#!/usr/bin/env node import { Server } from "@modelcontextprotocol/sdk/server/index.js"; import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; import { CallToolRequestSchema, ListToolsRequestSchema, } from "@modelcontextprotocol/sdk/types.js"; import { generateText } from "ai"; import { createOpenAI } from "@ai-sdk/openai"; import { createAnthropic } from "@ai-sdk/anthropic"; import { buildEvaluationPrompt } from "./prompt.js"; const server = new Server( { name: "prompt-evaluator", version: "1.0.0", }, { capabilities: { tools: {}, }, } ); // List available tools server.setRequestHandler(ListToolsRequestSchema, async () => { return { tools: [ { name: "evaluate", description: "Evaluate a prompt using AI analysis", inputSchema: { type: "object", properties: { prompt: { type: "string", description: "The prompt to evaluate", }, }, required: ["prompt"], }, }, { name: "ping", description: "Simple ping test to verify connection", inputSchema: { type: "object", properties: {}, }, }, ], }; }); // Helper to get the right model provider function getModel(modelName: string, apiKey: string) { // Map our simplified names to actual model IDs const modelMap: Record< string, { provider: "openai" | "anthropic"; modelId: string } > = { o3: { provider: "openai", modelId: "o3-2025-04-16" }, "opus-4": { provider: "anthropic", modelId: "claude-opus-4-20250514" }, "sonnet-4": { provider: "anthropic", modelId: "claude-sonnet-4-20250514" }, }; const model = modelMap[modelName]; if (!model) { throw new Error( `Unsupported model: ${modelName}. Use: o3, opus-4, or sonnet-4` ); } if (model.provider === "openai") { const openai = createOpenAI({ apiKey, baseURL: process.env.OPENAI_BASE_URL, }); return openai(model.modelId); } else { const anthropic = createAnthropic({ apiKey, baseURL: process.env.ANTHROPIC_BASE_URL, }); return anthropic(model.modelId); } } // Handle tool calls server.setRequestHandler(CallToolRequestSchema, async (request) => { switch (request.params.name) { case "ping": return { content: [ { type: "text", text: "Pong! MCP server is connected and working.", }, ], }; case "evaluate": const { prompt } = request.params.arguments as { prompt: string }; // Get config from environment variables const modelName = process.env.PROMPT_EVAL_MODEL || "sonnet-4"; const apiKey = process.env.PROMPT_EVAL_API_KEY; if (!apiKey) { return { content: [ { type: "text", text: "Error: PROMPT_EVAL_API_KEY not configured. Please set it in your .mcp.json file.", }, ], }; } try { const result = await generateText({ model: getModel(modelName, apiKey), prompt: buildEvaluationPrompt(prompt), maxTokens: 1000, }); return { content: [ { type: "text", text: result.text, }, ], }; } catch (error) { console.error("Error calling AI API:", error); throw new Error( `Failed to evaluate prompt: ${ error instanceof Error ? error.message : "Unknown error" }` ); } default: throw new Error(`Unknown tool: ${request.params.name}`); } }); async function main() { const transport = new StdioServerTransport(); await server.connect(transport); console.error("Prompt Evaluator MCP server running (with Vercel AI SDK)"); } main().catch((error) => { console.error("Server error:", error); process.exit(1); });