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What Grafana’s MCP screenshot tool does
get_panel_image asks Grafana to render a stored dashboard or panel and returns a PNG image. It is useful when you want an AI assistant or another MCP client to request a visual snapshot as part of a developer workflow, rather than manually exporting an image from the Grafana interface.
The tool is for Grafana dashboards and panels. It is not a general-purpose browser screenshot tool: the MCP server must connect to the Grafana instance, and image generation depends on Grafana’s rendering setup. The available tool reference describes rendering a stored dashboard or panel; it does not establish that the tool can capture arbitrary web pages.
Prerequisites before connecting an MCP client
- Grafana 9.0 or later. Grafana documents this as a prerequisite for the open-source MCP server.
- An MCP client. Examples include Claude Desktop, Cursor, and VS Code with Copilot. The client must be configured to connect to the MCP server using the transport you choose.
- A service-account token. The account needs
dashboards:readpermission for the dashboard or panel being requested. Use the least privilege that provides access to the intended dashboards. - Grafana Image Renderer. Grafana’s tool reference says the renderer service must be installed and configured for image generation.
- A reachable Grafana endpoint. The MCP server needs network access to the Grafana instance; a remote MCP client also needs access to the server’s selected transport endpoint.
Grafana documents installation by uvx, Docker, downloaded binary, or Helm. Choose one deployment method and one transport that fit where the client and server run. STDIO is intended for direct local integration; SSE and streamable HTTP expose network endpoints for clients that connect remotely.
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Install the Grafana MCP server with Docker
This minimal Docker pattern uses STDIO, suitable when the MCP client launches the server locally. Replace the example Grafana URL with the address reachable from the container, and replace the token value with the service-account token you created.
docker pull grafana/mcp-grafana
docker run --rm -i
-e GRAFANA_URL=http://localhost:3000
-e GRAFANA_SERVICE_ACCOUNT_TOKEN=<token>
grafana/mcp-grafana -t stdioBe careful with localhost: inside a container, it refers to the container itself, not necessarily the host running Grafana. If Grafana is on another host or is reachable under a different container-network name, set GRAFANA_URL to that reachable address. The precise networking value depends on your deployment.
For remote integrations, Grafana’s documentation also describes SSE, which exposes /sse, and streamable HTTP, which exposes /mcp. Use the official command variant for the chosen transport and configure the MCP client with the corresponding endpoint. The STDIO Docker command above is not a substitute for those network-server configurations.
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Connect the client and capture a dashboard or panel
- Start the server. Use your chosen installation method—Docker,
uvx, a downloaded binary, or Helm—and make sure its Grafana URL and service-account token are set for the target instance. - Register the server in the MCP client. Configure the client for STDIO if it launches a local process, or for the documented SSE or streamable HTTP endpoint if connecting over a network. Client setup screens and configuration-file locations vary by client.
- Check that rendering is enabled. If the server was started with the rendering category disabled,
get_panel_imagewill not be available. Also confirm that Grafana Image Renderer is installed and configured. - Ask for a specific image. In the client, request a PNG for the dashboard or panel you want. Identify the intended dashboard or panel clearly enough for the client to invoke
get_panel_imagewith the right target. - Review the returned image. The tool returns a PNG that the client workflow can display or save. Check that it is the expected dashboard or panel and that its rendered contents are usable for your purpose.
The permission requirement documented for get_panel_image is dashboards:read. Rendering tools can be disabled with --disable-rendering; Grafana also states that get_panel_image is unaffected by read-only mode if rendering remains enabled. Read-only mode should therefore not be confused with disabling rendering, and neither setting grants a service account dashboard access it does not have.
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Choose a deployment and transport
| Choice | Best fit | What to check |
|---|---|---|
| STDIO | A desktop MCP client that starts or communicates directly with a local server process. | Environment variables reach the process, and the process can reach Grafana and its renderer. |
| SSE | A client connecting to a network-exposed MCP server. | Use the SSE configuration and endpoint documented by Grafana; the endpoint path is /sse. |
| Streamable HTTP | A client connecting to the server over HTTP using that transport. | Use the matching server and client configuration; the endpoint path is /mcp. |
uvx, Docker, binary, or Helm |
Different ways to install or deploy the open-source server. | Choose a method compatible with your environment and make sure its network access and credentials are configured. |
Transport and deployment are separate decisions: Docker does not imply a particular client transport, for example. Choose the installation package based on how you operate the server, then configure the transport the client will actually use. For remote access, keep the endpoint exposure intentional and make sure the server can reach Grafana without exposing credentials unnecessarily.
Dashboard images versus panel images
The documented tool can render a stored dashboard or a panel as PNG. Choose the scope that answers the task: a panel image is more focused when the client needs one visualization; a dashboard image preserves the broader dashboard context. The tool description does not establish other output formats for this operation, so treat PNG as the supported result rather than assuming a PDF or another image format.
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For repeated or automated captures, be explicit about which stored dashboard or panel is intended. The available documentation summary does not specify additional capture parameters, scheduling behavior, image dimensions, or a guarantee about how dashboard variables or time ranges are selected. If a result depends on such details, confirm the behavior in your Grafana and MCP server versions rather than assuming the assistant will infer them.
Troubleshoot missing tools, authorization, and rendering
get_panel_image is not available
Check how the server was started. If it was launched with --disable-rendering, the rendering tool category is disabled. Remove that option or otherwise enable rendering, restart the server, and refresh or reconnect the MCP client so it sees the available tools.
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Verify that the token belongs to a service account and that its permissions include dashboards:read for the requested dashboard or panel. Also check that the server is pointed at the intended Grafana instance and that the configured token is the one you meant to use. Do not solve a narrow access issue by granting broader write permissions unless a separate task requires them.
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The call reaches Grafana but image generation fails
Verify that Grafana Image Renderer is installed, configured, and reachable from the Grafana setup that performs the render. A valid MCP connection and dashboard permission do not by themselves establish that the rendering service is working. Check the renderer configuration and connectivity before retrying the capture.
A remote client cannot connect
Confirm that the server was started for the same transport the client is configured to use. For SSE, verify the SSE endpoint; for streamable HTTP, verify the /mcp endpoint. Then check network exposure, routing, and whether the client can reach the server from its own environment. A local STDIO configuration will not provide a remote network endpoint by itself.
The image is for the wrong target or lacks expected context
Make the request more specific about the stored dashboard or panel. If your workflow depends on a particular dashboard state, variable, or time range, inspect the returned PNG and verify those details in your own environment. The documented tool summary does not specify every state-selection behavior, so do not infer that a capture will match a manually viewed dashboard without checking.
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Or skip the browser setup
For a website screenshot rather than Grafana’s server-side get_panel_image rendering, ScreenshotNeo offers a screenshot API and MCP server. It is a different capture path: point it at a web page that is reachable to the service; it does not replace Grafana MCP’s dashboard permission or renderer requirements. Its documented options include custom headers, cookies, and Authorization for pages that require them.
Here is a one-request cURL example using Grafana’s public website as the target. For your own dashboard, substitute its reachable page URL and configure access as needed:
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://grafana.com -o shot.webpSee the ScreenshotNeo documentation for API details. It accepts cookie or consent banners as a visitor and removes more than 60 known consent platforms, newsletter popups, and chat widgets before capture; those steps can be turned off. Bot checks and CAPTCHAs, blank pages, timeouts, failed loads, and cache hits are not billed, and responses identify the page verdict and billing status in headers. Its MCP server provides take_screenshot, get_page_info, and capture_pdf for AI-agent workflows. The Free plan includes 1,000 shots a month with no card; paid plans start at $5 for 3,000 shots.
Sign up for ScreenshotNeo’s free plan to try 1,000 screenshots a month without a card.
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For Grafana MCP, the central reliability dependency is the full rendering path: MCP client to server, server to Grafana, and Grafana to its Image Renderer. A successful connection at one layer does not prove the other layers are healthy. When building an operational workflow, check that the service-account token can still read the intended dashboards and that the renderer remains reachable after deployment changes.
Keep the service-account scope as narrow as practical. The documented permission for this tool is dashboard read access; image rendering does not require treating an AI client as a Grafana administrator. Protect the token as a secret in the deployment environment, and avoid copying it into prompts or logs. The source material does not state a per-render cost, a latency target, or a throughput limit for Grafana MCP, so those values should be established for your own Grafana and renderer deployment rather than assumed.
When image capture is part of a larger agent workflow, treat the returned PNG as an output to inspect, not proof that every dashboard value is correct or current. Validate the selected dashboard state and the underlying Grafana data according to the needs of the task.
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