How to Use the Grafana MCP in VS Code Copilot

Q: How do teams use Grafana with VS Code Copilot?

Add the server to your .vscode/mcp.json file. This allows everyone on your team to use firingalerts and other tools directly within the chat.

Q: Can I search for Grafana dashboards in VS Code?

Yes, use searchdashboards to find the correct UID. You can then use getdashboard to inspect the underlying panel queries for your current task.

Q: Does VS Code Copilot support listing Grafana datasources?

It does. Developers can call listdatasources to see the full list of connected backends, ensuring everyone knows which systems are being monitored.

Standardize team observability by connecting Grafana to VS Code Copilot via shared MCP configurations.

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Connect Grafana MCP to VS Code Copilot

Create your Vinkius account to connect Grafana to VS Code Copilot and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Grafana with VS Code Copilot

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Team-wide alert monitoring in VS Code

Commit your MCP config to the repo so every developer uses `firing_alerts` to check system health. This ensures the entire team sees the same production incidents. Your agent uses this shared view to keep everyone aligned during an outage. It provides a common source of truth for all engineers working on the same codebase.

Shared dashboard access in VS Code

Use `search_dashboards` and `get_dashboard` to pull panel configurations into your workspace. This makes it easy for the team to reference production metrics while writing code. Standardizing these tools across the team means everyone debugs using the same dashboard logic. You stop wasting time on inconsistent metric definitions.

Sync datasource visibility in VS Code

Run `list_datasources` to show the team exactly which backends are active. This prevents confusion when different engineers work on services tied to different databases. It keeps your observability documentation in sync with your actual infrastructure. Everyone sees the same list of available data sources every time they run the tool.

Setup guide

Set up Grafana MCP in VS Code Copilot

Prerequisites

VS Code 1.99 or later with GitHub Copilot extension
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and run "MCP: Add Server". Select HTTP (Streamable) as the server type. VS Code will create .vscode/mcp.json in your workspace.
2

Add the Grafana MCP

Paste the JSON snippet shown on the right into your .vscode/mcp.json. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Switch to Agent mode

Open Copilot Chat (Cmd+Shift+I / Ctrl+Shift+I) and switch to Agent mode using the dropdown. MCP tools are only available in Agent mode — they do not appear in Edit or Ask modes.
4

Verify the connection

In the Copilot Chat input, type # to list available tools. You should see the Grafana tools listed. Try asking: "List my recent Grafana transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "grafana-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about Grafana MCP in VS Code Copilot

Add the server to your `.vscode/mcp.json` file. This allows everyone on your team to use `firing_alerts` and other tools directly within the chat.

Yes, use `search_dashboards` to find the correct UID. You can then use `get_dashboard` to inspect the underlying panel queries for your current task.

It does. Developers can call `list_datasources` to see the full list of connected backends, ensuring everyone knows which systems are being monitored.

The server uses endpoint token authentication for every request. Because the setup is managed via your repo config, you maintain full control over who accesses your observability tools.

The server only reads dashboard layouts, alert rule states, and datasource metadata. It is restricted from accessing or exporting your raw time-series metric history.

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