Show HN: Echos – A lightweight multi-agent AI system with pre-built agents https://ift.tt/tKs8a5Q

Show HN: Echos – A lightweight multi-agent AI system with pre-built agents Hi all, I'm Dante, and I'm building Echos, a platform that gives you pre-built AI agents so you can stop rebuilding orchestrators, database agents, and retry logic every time. What it does: - Pre-built agents: Database queries, API calls, web search, data analysis, code generation. - YAML-based workflows: Define your agent architecture without rebuilding orchestrators. - Built-in guardrails: SQL injection protection, SSRF blocking, table/domain whitelisting. - Visual traces: See what happened, where it failed, and how much it cost. Why I built it: Every time I build a multi-agent system, I spend 2-3 weeks creating the same infrastructure: orchestrators that route tasks, database agents with SQL guardrails, retry logic, loop limiting, and cost tracking. Then another week of debugging when things break. I wanted to ship features, not plumbing. Most frameworks are bulky and complex. You just want pre-built components you can compose like AWS services. What Echos gives you: - Ship faster: Pre-built agents you compose in YAML. - Debug in minutes: Visual traces show exactly what happened, where it failed, and how much it cost. - Prevent disasters: Built-in guardrails (SQL injection protection, SSRF blocking, loop limiting) catch 80% of dangerous operations. - Control costs: Per-agent spending limits prevent runaway bills. Try it: Clone https://ift.tt/Z2aTOVv or go to https://echoshq.com import { EchosRuntime } from '@echoshq/runtime'; const runtime = new EchosRuntime({ apiKey: process.env.ECHOS_API_KEY, apiUrl: process.env.ECHOS_API_URL, workflow: './workflow.yaml' // Define agents and routes in YAML }); // Simple usage await runtime.run({ task: 'Analyze customer churn', memory: { year: 2024, region: 'north' } }); Tech: - NestJS for the backend API: Needed structured DI and middleware for auth. - Postgres for trace storage: JSON columns for flexible span logs, native SQL performance. - Resend for magic link authentication: Reliable email delivery without managing SMTP. - Nuxt 3 for the dashboard: SSR for fast initial load, client-side interactivity for live traces. - Railway for deployment: Fast deploys. First time trying it. My previous default is Digital Ocean. What I learned: - Time saved is the real value: Teams don't want another framework, they want to ship faster. - Debugging is 50% of the work: Visual traces that show the full execution path are essential. - Simple guardrails work: Blocking DELETE/DROP and unknown domains catches most disasters. - YAML > Code for config: Non-engineers can edit workflows without touching code. Looking for feedback: - Does this solve a real problem for you? - Which agents would you use most? database, API calls, web search, data analysis, or code generation? - Is YAML configuration expressive enough, or do you need more programmatic control? - What agents should we add next? (GitHub, Slack, email, cloud APIs?) - Would you use this for autonomous agents, or just one-off tasks? - Would this save you time on your next multi-agent project? - What's missing that would make this immediately useful? Thank you! https://ift.tt/Z2aTOVv November 10, 2025 at 05:52PM