MCP server for Grafana

MCP server for Grafana is an application that provides AI assistants with access to Grafana via the standard Model Context Protocol (MCP). The server is deployed on a virtual machine in Yandex Cloud and connects to an existing Grafana instance.

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.
• AI Assistant Integration. Enables Claude, ChatGPT, and other AI models to interact with Grafana: search and analyze dashboards, view data sources, explore metrics and alerts.
• Bearer Token Authorization. All requests to the MCP server are protected with a Bearer token stored in Yandex Lockbox.
• Secure Secret Storage. The Grafana API key is stored in Yandex Lockbox and retrieved at startup.
• Standard MCP Protocol. Uses the open Model Context Protocol for AI model interaction, ensuring compatibility with a wide range of clients.
• HTTP Transport. The MCP server is accessible on port 8000 (HTTP), simplifying integration with various clients and tools.
• Minimal Resources. The application runs on a virtual machine with minimal configuration (2 vCPU, 2 GB RAM), reducing infrastructure costs.

1. Make sure you have a running Grafana instance with API access.
2. Create a service account token in Grafana with the necessary access permissions.
3. Create a secret in Yandex Lockbox to store the Grafana API key. The secret must contain an api_key key with the Grafana service account token value.
4. 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.
5. Create a service account with the roles compute.editor, iam.serviceAccounts.admin, lockbox.payloadViewer, vpc.admin (the admin role includes all the specified roles).
6. In the management console select the Cloud Apps service.
7. In the left panel, select Application Store.
8. Select MCP Grafana 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.
   • Grafana instance URL.
   • Lockbox secret ID containing the Grafana API key.
   • (Optional) A certificate from Yandex Certificate Manager for connecting to a self-hosted Grafana instance over HTTPS.
10. Click the Install button and wait for the application to install.
11. After installation, the MCP server will be available at http://<vm-ip>:8000.
12. 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.

• Searching and analyzing Grafana dashboards using an AI assistant (Claude, ChatGPT).
• Viewing and exploring data sources configured in Grafana.
• Analyzing alerts and notification rules via natural language.
• Exploring metrics and dashboard panels with AI.
• Automating routine monitoring tasks through an AI assistant.

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.