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TypeScript MCP server

Example of how to Actorize a STDIO Model Context Protocol server.

Language

typescript

Tools

mcp

Features

Run on ApifyUse locally

src/main.ts

src/billing.ts

1/**
2 * MCP Server - Main Entry Point
3 *
4 * This file serves as the entry point for the MCP Server Actor.
5 * It sets up a proxy server that forwards requests to the locally running
6 * MCP server, which provides a Model Context Protocol (MCP) interface.
7 */
8

9// Apify SDK - toolkit for building Apify Actors (Read more at https://docs.apify.com/sdk/js/)
10import { Actor, log } from 'apify';
11import { stdioToSse } from './lib/server.js';
12import { getLogger } from './lib/getLogger.js';
13

14// This is an ESM project, and as such, it requires you to specify extensions in your relative imports
15// Read more about this here: https://nodejs.org/docs/latest-v18.x/api/esm.html#mandatory-file-extensions
16// Note that we need to use `.js` even when inside TS files
17// import { router } from './routes.js';
18

19// Configuration constants for the MCP server
20// Command to run the Sequential Thinking MCP server
21// TODO: Do not forget to install the MCP server in package.json (using `npm install ...`)
22const MCP_COMMAND = 'npx @modelcontextprotocol/server-sequential-thinking';
23

24// Check if the Actor is running in standby mode
25const STANDBY_MODE = process.env.APIFY_META_ORIGIN === 'STANDBY';
26const SERVER_PORT = parseInt(process.env.ACTOR_WEB_SERVER_PORT || '', 10);
27

28// Logger configuration
29const LOG_LEVEL = 'info';
30const OUTPUT_TRANSPORT = 'sse';
31

32// Initialize the Apify Actor environment
33// The init() call configures the Actor for its environment. It's recommended to start every Actor with an init()
34await Actor.init();
35

36// Charge for Actor start
37await Actor.charge({ eventName: 'actor-start' });
38

39if (!STANDBY_MODE) {
40    // If the Actor is not in standby mode, we should not run the MCP server
41    const msg = 'This Actor is not meant to be run directly. It should be run in standby mode.';
42    log.error(msg);
43    await Actor.exit({ statusMessage: msg });
44}
45

46const logger = getLogger({
47    logLevel: LOG_LEVEL,
48    outputTransport: OUTPUT_TRANSPORT,
49});
50await stdioToSse({
51    port: SERVER_PORT,
52    stdioCmd: MCP_COMMAND,
53    logger,
54});

MCP server template

A template for running and monetizing a Model Context Protocol server over stdio on Apify platform. This allows you to run any stdio MCP server as a standby Actor and connect via SSE transport with an MCP client.

How to use

Change the MCP_COMMAND to spawn your stdio MCP server in src/main.ts, and don't forget to install the required MCP server in the package.json (using npm install ...). By default, this template runs a Sequential Thinking MCP Server server using the following command:

npx @modelcontextprotocol/server-sequential-thinking

Feel free to configure billing logic in .actor/pay_per_event.json and src/billing.ts.

Push your Actor to the Apify platform, configure standby mode, and then connect to the Actor standby URL with your MCP client (e.g., https://me--my-mcp-server.apify.actor/sse).

Pay per event

This template uses the Pay Per Event (PPE) monetization model, which provides flexible pricing based on defined events.

To charge users, define events in JSON format and save them on the Apify platform. Here is an example schema with the tool-request event:

[
    {
        "tool-request": {
            "eventTitle": "Price for completing a tool request",
            "eventDescription": "Flat fee for completing a tool request.",
            "eventPriceUsd": 0.05
        }
    }
]

In the Actor, trigger the event with:

await Actor.charge({ eventName: 'tool-request' });

This approach allows you to programmatically charge users directly from your Actor, covering the costs of execution and related services.

To set up the PPE model for this Actor:

  • Configure Pay Per Event: establish the Pay Per Event pricing schema in the Actor's Monetization settings. First, set the Pricing model to Pay per event and add the schema. An example schema can be found in .actor/pay_per_event.json.

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