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Turning an Existing Express API into a Conversational Backend (Konsier Integration)

In Part 2, I broke down the architecture behind conversational systems: Agents → Tools → Backend → Channels Now let’s make it real. In this post, I’ll walk through how I integrated this model into an existing Express API using Konsier. …

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In Part 2, I broke down the architecture behind conversational systems:



Agents → Tools → Backend → Channels



Now let’s make it real.



In this post, I’ll walk through how I integrated this model into an existing Express API using Konsier.



No rewrite.

No new backend.



Just layering a conversational interface on top of what already exists.







Starting Point



I already had a simple Express + PostgreSQL backend.



It exposed endpoints like:




GET /menu
POST /orders
GET /orders/:id
PATCH /orders/:id






Typical setup:




Client → Express API → Database






The goal was:




Allow users to interact with this backend through chat (Telegram, WhatsApp, etc.)




without rewriting the API.









What Changes (and What Doesn’t)



The important thing to understand:



Your backend stays the same.



You’re not replacing your API.



You’re adding a new layer:




User (chat)

Konsier

Express API

Database












Step 1 — Install Konsier






npm install konsier






If you're using Express:




npm install express












Step 2 — Define Your First Tool



Tools are how your agent interacts with your backend.



Start with something simple like fetching the menu.



```ts id="tool1"

import { Konsier } from "konsier";

import { z } from "zod";



const getMenu = Konsier.tool({

name: "get_menu",

description: "Returns all menu items",



input: z.object({

category: z.string().optional(),

}),



handler: async (input) => {

const items = await db.query("SELECT * FROM menu_items");

return { items: items.rows };

},

});






This is just a wrapper around your existing logic.

---

## Step 3 — Configure the Agent

Now define an agent that can use this tool.



```ts id="agent1"
const konsier = new Konsier({
apiKey: process.env.KONSIER_API_KEY!,

endpointUrl: "https://your-public-url.com/konsier",

agents: {
customer_support: {
name: "Customer Support",
description: "Helps users browse the menu",

systemPrompt: "You help users find food and place orders.",

tools: [getMenu],
},
},
});





The agent decides when to call get_menu.







Step 4 — Mount the Webhook



This is the connection point between Konsier and your backend.



```ts id="webhook1"

import express from "express";

import { serveKonsier } from "konsier/express";



const app = express();



serveKonsier(app, konsier);






This automatically:

* creates the webhook route
* validates requests
* routes messages to your agent

---

## Step 5 — Sync Your Configuration

Start your server and sync:



```ts id="sync1"
app.listen(3000, async () => {
await konsier.sync();
console.log("Server running");
});





This pushes your local agent + tools config to Konsier Cloud.







Step 6 — Connect a Channel



In the Konsier dashboard:




  1. Create a project

  2. Add your API key

  3. Set your public /konsier endpoint

  4. Link your agent

  5. Connect a channel (Telegram, Slack, etc.)



Now send a message like:




“What food do you have?”




Your agent will automatically call get_menu.







End-to-End Flow



Here’s what happens when a user sends a message:




User → Telegram

Konsier

/konsier webhook

Agent

Tool (get_menu)

Database

Response → User












Key Takeaway



You didn’t rebuild your backend.



You didn’t duplicate logic.



You simply exposed your existing functionality as tools.



That’s the power of this approach.









What’s Next



So far we’ve only used a simple read operation (get_menu).



But real systems need more:




  • creating orders

  • updating orders

  • tracking status

  • handling edge cases



In Part 4, we’ll go deeper into tool design:




  • how to structure tools properly

  • how to validate inputs

  • how to avoid breaking your backend

  • and how to handle real business logic






If you're already running an Express backend, you're closer than you think to having a conversational interface.



In the next post, we’ll build real tools on top of it.

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