Skip to main content
Glama

Ultra MCP

fast-completion-path.test.ts1.45 kB
import { describe, it, expect, beforeEach } from 'vitest'; import { trackLLMRequest, updateLLMCompletion } from '../../db/tracking'; import { getDatabase } from '../../db/connection'; import { llmRequests } from '../../db/schema'; import { eq } from 'drizzle-orm'; import { ensureDatabaseReady } from '../../db/migrate'; describe('Fast completion path', () => { beforeEach(async () => { await ensureDatabaseReady(); try { const db = await getDatabase(); await db.delete(llmRequests).execute(); } catch {} }); it('should persist completion even when called immediately after track', async () => { const startTime = Date.now(); const requestId = await trackLLMRequest({ provider: 'openai', model: 'gpt-4', requestData: { prompt: 'hi' }, startTime, }); // Immediately update completion (fast path) await updateLLMCompletion({ requestId, responseData: { text: 'hello' }, usage: { promptTokens: 1, completionTokens: 2, totalTokens: 3 }, finishReason: 'stop', endTime: Date.now(), }); const db = await getDatabase(); const rows = await db.select() .from(llmRequests) .where(eq(llmRequests.id, requestId)) .execute(); expect(rows).toHaveLength(1); const rec = rows[0]; expect(rec.totalTokens).toBe(3); expect(rec.status).toBe('success'); expect(rec.responseData?.text).toBe('hello'); }); });

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RealMikeChong/ultra-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server