Google Cloud Logging Stream Connector for AI agents.
1 live capability
Give your agent surgical access to your GCP logs for faster production troubleshooting.
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Why people use Google Cloud Logging Stream
Google Cloud Logging Stream for Faster Production Troubleshooting
With this Connector, you can just tell your agent to find the error. It handles the heavy lifting of searching the log streams and parsing the data for you. You get the answer in seconds, allowing you to focus on fixing the problem instead of hunting for it.
What Vinkius changes
You give your agent eyes on your logs without giving it the keys to your entire cloud.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Debugging a production outage
An SRE notices a spike in 500 errors.
- Real-world use case 02
Tracing a specific user issue
A support engineer needs to know why a specific user's payment failed.
- Real-world use case 03
Monitoring traffic spikes
A DevOps engineer wants to see if a recent deployment caused a traffic anomaly.
Complete set · 1capability
The complete Google Cloud Logging Stream capability set.
These are the exact actions your AI can choose when you ask it to work with Google Cloud Logging Stream.
01
1 capability in this set.
Part of 1 available through Google Cloud Logging Stream.
- 01 Capability
Stream logs
Read and search log entries from a configured Google Cloud Log. Use advanced GCP Logging filter syntax to narrow down results.
Set up in minutes
One URL. Then ask Google Cloud Logging Stream to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Google Cloud Logging Stream from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_WvvXmnhnniAUbHWunSoDvbFnG63nFsN7jFywz4oj/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Google Cloud Logging Stream, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Google Cloud Logging Stream for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_WvvXmnhnniAUbHWunSoDvbFnG63nFsN7jFywz4oj/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Google Cloud Logging Stream URL.
- Step 03
Save and start
Save the connection and enable Google Cloud Logging Stream in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"google-cloud-logging-stream": {
"url": "https://edge.vinkius.com/vk_preview_WvvXmnhnniAUbHWunSoDvbFnG63nFsN7jFywz4oj/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Google Cloud Logging Stream
Open Agent mode in chat and ask: "Using Google Cloud Logging Stream, help me...". 1 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"google-cloud-logging-stream": {
"url": "https://edge.vinkius.com/vk_preview_WvvXmnhnniAUbHWunSoDvbFnG63nFsN7jFywz4oj/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Google Cloud Logging Stream
Ask Copilot: "Using Google Cloud Logging Stream, help me...". 1 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"google-cloud-logging-stream": {
"url": "https://edge.vinkius.com/vk_preview_WvvXmnhnniAUbHWunSoDvbFnG63nFsN7jFywz4oj/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Google Cloud Logging Stream
Open Cascade and ask: "Using Google Cloud Logging Stream, help me...". 1 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"google-cloud-logging-stream": {
"url": "https://edge.vinkius.com/vk_preview_WvvXmnhnniAUbHWunSoDvbFnG63nFsN7jFywz4oj/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Google Cloud Logging Stream
Ask Cline: "Using Google Cloud Logging Stream, help me...". 1 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add google-cloud-logging-stream --transport http "https://edge.vinkius.com/vk_preview_WvvXmnhnniAUbHWunSoDvbFnG63nFsN7jFywz4oj/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Google Cloud Logging Stream
Ask Claude: "Using Google Cloud Logging Stream, show me...". 1 tools are ready
Where the request belongs
Work Google Cloud Logging Stream can move forward.
This is for the engineers who are tired of manual log hunting and need a secure way to let their agents help with production issues.
Site Reliability Engineer (SRE)
Uses this to quickly identify the source of a production outage during a high-pressure incident.
DevOps Engineer
Checks for infrastructure anomalies and traffic spikes to ensure system stability.
Backend Developer
Queries logs for specific user IDs or failed webhooks to debug individual customer issues.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Loggly (Cloud Log Management API)
Manage cloud logs via Loggly. send events, execute Lucene searches, and analyze infrastructure metrics directly from your AI agent.
Papertrail (Real-time Cloud Log Manager)
Manage and analyze cloud logs in real-time via Papertrail. search events, list systems, and organize log groups directly from your AI agent.
Amazon CloudWatch Log Group
This MCP does exactly one thing: it queries logs from a single CloudWatch Log Group. That's its only function, and nothing else. Incredible for giving your AI secure observability.
Logz.io
Query logs, manage alerts, and monitor triggered events in Logz.io directly from your AI agent using Elasticsearch DSL.
HyperDX (Open Source Observability)
Monitor logs, events, and alerts via HyperDX. search logs, manage alert rules, and inspect dashboards directly from your AI agent.
Bring your own AI
Change the model, client or framework. Keep Google Cloud Logging Stream connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Google Cloud Logging Stream.
The practical details behind the request, access and result.
Can the Google Cloud Logging Stream MCP see my billing data?
No, this Connector is strictly for log observability. It doesn't have access to your billing, project settings, or any other sensitive cloud management data.
How does the Google Cloud Logging Stream MCP handle permissions?
It uses scoped access. This means your agent only sees the specific logs you've configured it to query, keeping the rest of your cloud environment private.
Can I use custom filters with the Google Cloud Logging Stream MCP?
Yes, it supports full Cloud Logging syntax. You can filter by severity, specific resources, or any other custom criteria you use in the GCP console.
Does the Google Cloud Logging Stream MCP work with my existing GCP setup?
Yes, it works with your current environment. It just provides a way for your agent to query those existing logs using the native GCP capabilities.
How do I use the Google Cloud Logging Stream MCP to find specific errors?
You can simply ask your agent to search for errors. It will use the capability to filter for high-severity logs and summarize the findings for you.
Why limit the agent to a single Log Name?
To enforce zero-trust security. An autonomous AI agent debugging an application shouldn't have access to read your organization's entire audit log history, IAM logs, or logs from other unrelated services.
Can I use advanced GCP Log queries?
Yes! You can pass any standard GCP Logging filter (e.g., textPayload:"Exception" or jsonPayload.status="500") via the filter argument. The server automatically merges your filter with the strict logName restriction.
How are the results ordered?
Results are always returned in descending order (timestamp desc), meaning the AI agent gets the most recent logs first, which is ideal for real-time debugging.
One connection away
Give your agent a direct line to Google Cloud Logging Stream.
Connect Google Cloud Logging Stream once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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