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.
• Dynamic Actor Discovery. The AI agent can find and add new Actors from the Apify Store on the fly.
• Datasets and Storages Access. Work with Apify key-value store, request queue, and dataset.
• 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.
• HTTP with SSE Transport. The MCP server is accessible on port 8000 (HTTP with SSE).
• 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 with the roles compute.editor, iam.serviceAccounts.admin, lockbox.payloadViewer, vpc.admin (the admin role includes all the specified roles).
5. In the management console select the Cloud Apps service.
6. In the left panel, select Application Store.
7. Select MCP Apify and click the Use button.
8. 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.
9. Click the Install button and wait for the application to install.
10. After installation, the MCP server will be available at http://<vm-ip>:8000.
11. Configure your AI client (Claude Desktop, Cursor, etc.) 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 the AI Studio service and go to the MCP Hub section.
2. Click Create MCP server and choose the External MCP server type.
3. Specify the server name and the ID of the VPC network where the MCP server virtual machine is deployed. The network ID is available on the application page in the Application data section, VPC network ID field.
4. At the MCP server connection step, fill in the parameters with the values from the Application data section:
   • MCP server type — value from the MCP server type field.
   • MCP server URL — value from the MCP server URL (internal) field.
   • In the HTTP headers block, add an Authorization header with the value Bearer <bearer_token>, where <bearer_token> is the token from the Yandex Lockbox secret specified during application installation.
5. Click Connect. After a successful connection check, select the required tools and click Connect — 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.