MCP server for Apify

MCP server for Apify is an application that provides AI assistants with access to the Apify ecosystem — the world’s largest marketplace of tools for web scraping, data extraction, and web automation. The server is deployed on a virtual machine in Yandex Cloud and interacts with AI models via the standard Model Context Protocol (MCP).

Key Features and Benefits

• Yandex AI Studio Integration. The MCP server integrates with AI Studio MCP Servers — connect it to your AI agents in just a few clicks.
• Access to 6000+ Apify Actors. The AI assistant can run ready-made Actors from the Apify Store: parsers for social networks, e-commerce, search engines, maps, and other sites.
• Web Scraping and Data Extraction. Extract structured data from any website using prebuilt or custom Actors.
• Actor Discovery and Execution. The AI agent can find Actors from the Apify Store and run them through server tools.
• Access to Datasets and Storage. Work with Apify key-value stores and datasets.
• Bearer Token Authorization. All requests to the MCP server are protected with a Bearer token stored in Yandex Lockbox.
• Secure Secret Storage. The Apify API token is stored in Yandex Lockbox and retrieved at startup.
• Standard MCP Protocol. Uses the open Model Context Protocol for AI model interaction.
• Streamable HTTP Transport. The MCP server is accessible on port 8000 (Streamable HTTP).
• Minimal Resources. The application runs on a virtual machine with minimal configuration (2 vCPU, 2 GB RAM).
• Docker Containerization. The server runs in Docker containers (MCP + supergateway + nginx auth proxy).

1. Obtain an Apify API token: sign up at apify.com and create a token in the Integrations section.
2. Create a secret in Yandex Lockbox to store the Apify API token. The secret must contain an api_token key with the token value.
3. Create a secret in Yandex Lockbox to store the Bearer token for authorization. The secret must contain a bearer_token key with an arbitrary token value.
4. Create a service account for deploying the application and assign it the roles compute.editor, iam.serviceAccounts.admin, and vpc.admin on the deployment folder.
5. Assign the installer service account the lockbox.admin role separately on the Apify API token secret and the Bearer token secret. This role is required to read and modify access permissions on these secrets; no folder-level Lockbox role is required. This also applies to secrets in another folder. During installation, the application creates a dedicated VM service account and grants it lockbox.payloadViewer only on the selected secrets.
6. In the management console select the Cloud Apps service.
7. In the left panel, select Application Store.
8. Select MCP server for Apify and click the Use button.
9. Specify:
   • Application name.
   • (Optional) Application description.
   • The service account created earlier.
   • The cloud subnet where the virtual machine will be deployed.
   • Lockbox secret ID containing the Bearer token for authorization.
   • Lockbox secret ID containing the Apify API token.
   • External access to the MCP server (optional; disabled by default, enable for connections through the public IP address).
   • SSH access: Disabled or Enabled. If enabled, specify a username and an SSH public key. Enabling SSH exposes TCP port 22 to the internet; use a temporary key and keep SSH disabled when it is not required.
10. Click the Install button and wait for the application to install.
11. After installation, copy the full URL from Application data, MCP server URL (internal): http://<private-ip>:8000/mcp. The client needs network access to the VM’s internal IP address.
12. Configure your AI client to connect to the MCP server, specifying the Authorization: Bearer <your-token> header.

Connecting the MCP server to Yandex AI Studio

1. In the management console open AI Studio and go to Agent Core → MCP servers.
2. Click Create MCP server and select the required MCP server under MCP servers from Yandex Cloud Marketplace.
3. Specify the server name and select an existing application instance, or create a new one by following the deployment instructions. When deploying a new server, the Save button becomes available only after the MCP server has been fully deployed and started.
4. After you select the application, the MCP server’s Network and Service account settings are filled in automatically.
5. Click Create. After the connection has been verified successfully, select the required tools and click Save. The MCP server will be registered in AI Studio and available for use by AI agents.

• Scraping products from e-commerce sites and marketplaces via ready-made Apify Actors.
• Extracting data from social networks (Instagram, TikTok, Twitter/X, LinkedIn, Facebook) for analytics and monitoring.
• Parsing search results from Google, Bing, and maps.
• Collecting reviews, prices, and product specifications to build comparison tables.
• Automated website monitoring and data collection into Apify datasets via an AI agent.

Yandex Cloud technical support is available 24/7. The types of requests you can submit and the appropriate response time depend on your pricing plan. You can switch to the paid support plan in the management console. You can learn more about the technical support terms here.