How to Use the Google Cloud Logging Stream MCP in Windsurf

Q: How do I configure Google Cloud Logging Stream in Windsurf?

Open your /.codeium/windsurf/mcpconfig.json file and add the server configuration under the mcpServers key in your MCP configuration. Alternatively, use the Settings panel, navigate to Cascade, and add the server via the UI.

Feed live GCP log data directly to Windsurf Cascade so it can diagnose and fix production errors on its own.

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Connect Google Cloud Logging Stream MCP to Windsurf

Create your Vinkius account to connect Google Cloud Logging Stream to Windsurf 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 Google Cloud Logging Stream with Windsurf

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Cascade debugs production errors using live telemetry

The `stream_logs` tool gives Windsurf Cascade direct access to your Google Cloud Logging environment without leaving the IDE. Cascade uses this telemetry to inspect actual runtime behavior instead of guessing why a deployment failed. When a test fails, Cascade pulls the exact backend trace. It reads the error payload, locates the broken line of code, and applies the fix in one autonomous run.

Real-time filtering with this Google Cloud Logging MCP Server

This Google Cloud Logging MCP Server exposes the `stream_logs` tool to target specific errors by feeding GCP filter queries directly to Cascade. You can narrow down the noise using standard syntax like severity>=ERROR or resource.type=gce_instance. Cascade uses these targeted streams to monitor application health during local testing or staging runs. You get immediate feedback on whether your latest commit resolved the issue.

Run multi-step diagnostic loops in Windsurf

The `stream_logs` tool enables Cascade to build its own debugging pipeline from scratch. It executes a query, analyzes the payload, and adjusts its search parameters based on what it finds. You set the high-level goal, and the agent handles the repetitive step-by-step log hunting. It stops only when it identifies the root cause of the incident.

Setup guide

Set up Google Cloud Logging Stream MCP in Windsurf

Prerequisites

Windsurf IDE installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Click the Cascade assistant icon in the sidebar, then click the hammer icon (🔨) at the top of the panel. Select "Configure" to open ~/.codeium/windsurf/mcp_config.json.
2

Add the Google Cloud Logging Stream MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Refresh MCPs

Go back to the hammer icon (🔨) in Cascade and click "Refresh". Windsurf will detect the new server. No full restart is needed — the connection is hot-reloaded.
4

Verify in Cascade

Start a new Cascade conversation and ask something like "Show my Google Cloud Logging Stream payment history." If connected, Cascade will call the Google Cloud Logging Stream tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json

{
  "mcpServers": {
    "google-cloud-logging-stream-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Cloud Logging Stream. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Google Cloud Logging Stream MCP in Windsurf

Open your ~/.codeium/windsurf/mcp_config.json file and add the server configuration under the mcpServers key in your MCP configuration. Alternatively, use the Settings panel, navigate to Cascade, and add the server via the UI.

Yes, Cascade chains log inspection tasks without asking for manual confirmation at every step. It calls the log stream, reads the payload, and decides what to do next based on the error data.

No, the connection runs through a lightweight V8 sandbox that keeps this MCP connection fast and isolated. Your IDE performance remains unaffected even when streaming large volumes of telemetry.

Your configured service account needs the Logging Viewer role in Google Cloud. This provides the minimum read access required to execute queries.

Your GCP log entries and payload data stay local to your environment and the V8 sandbox. Vinkius uses ephemeral execution environments, meaning no telemetry is stored or cached on our servers after the session ends.

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