My MCP Server

My MCP Server

A template for deploying and monetizing MCP servers on Apify, supporting stdio and streamable HTTP transports with authentication and pay-per-event billing.

Category
访问服务器

README

MCP server template

<!-- This is an Apify template readme -->

▶️ Try it live on Apify Store

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

Note: the check_dependency_tree_risk tool only scans the first 100 packages found in a package-lock.json and only returns details for Medium-severity-or-above findings, to keep results bounded on very large dependency trees.

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 an Everything MCP Server using the following command:

const MCP_COMMAND = [
    'npx',
    '@modelcontextprotocol/server-everything',
];

Alternatively, you can use the mcp-remote tool to turn a remote MCP server into an Actor. For example, to connect to a remote server with authentication:

const MCP_COMMAND = [
    'npx',
    'mcp-remote',
    'https://mcp.apify.com',
    '--header',
    'Authorization: Bearer TOKEN',
];

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 using the endpoint: https://me--my-mcp-server.apify.actor/mcp (streamable HTTP transport).

Important: When connecting to your deployed MCP server, you must pass your Apify API token in the Authorization header as a Bearer token. For example:

Authorization: Bearer <YOUR_APIFY_API_TOKEN>

This is required for authentication and to access your Actor endpoint.

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 pay_per_event.json.

Resources

Getting started

For complete information see this article. To run the Actor use the following command:

apify run

Deploy to Apify

Connect Git repository to Apify

If you've created a Git repository for the project, you can easily connect to Apify:

  1. Go to Actor creation page
  2. Click on Link Git Repository button

Push project on your local machine to Apify

You can also deploy the project on your local machine to Apify without the need for the Git repository.

  1. Log in to Apify. You will need to provide your Apify API Token to complete this action.

    apify login
    
  2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under Actors -> My Actors.

    apify push
    

Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选