MCP server for n8n

MCP server for n8n is an application that provides AI assistants with access to the n8n workflow automation platform via the standard Model Context Protocol (MCP). The server is deployed on a virtual machine in Yandex Cloud.

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.
• Workflow Management. Create, update, validate, and run n8n workflows through an AI assistant.
• Access to 500+ n8n Nodes. Information about all available nodes, their documentation, parameters, and usage examples.
• Workflow Templates. Search and use ready-made templates to quickly build automations.
• Validation and Auto-fix. Check workflow structure, connections, and expressions with automatic error correction.
• Bearer Token Authorization. All requests to the MCP server are protected with a Bearer token stored in Yandex Lockbox.
• Secure Secret Storage. The n8n API key is stored in Yandex Lockbox and retrieved at startup.
• Standard MCP Protocol. Uses the open Model Context Protocol for AI model interaction.
• HTTP Transport. The MCP server is accessible on port 8000 (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 + nginx auth proxy).

1. Prepare an n8n instance: deploy n8n (self-hosted or cloud) and create an API key in the instance settings (Settings → API).
2. Create a secret in Yandex Lockbox to store the n8n API key. The secret must contain an api_key key with the API key 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 n8n 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 n8n API key.
   • n8n instance URL (e.g., https://your-n8n.example.com).
   • (Optional) Certificate from Yandex Certificate Manager for HTTPS connection to n8n.
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.

• Creating and configuring n8n workflows through an AI assistant (Claude, ChatGPT).
• Browsing n8n node documentation and searching for suitable automation templates.
• Validating and automatically fixing errors in workflows.
• Managing workflow execution: running, viewing history, deleting records.
• Building AI agents that automate business processes through n8n.

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.