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Google Cloud Observability MCP Server
for AI Agents
Production-ready Google Cloud Observability MCP server with 45 extensible actions — plus built-in authentication, security, and optimized execution.
Google Cloud Observability MCP Server
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StackOne
StackOne 
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45 Agent Actions
Create, read, update, and delete across Google Cloud Observability — and extend your agent's capabilities with custom actions.
Authentication
Agent Tool Authentication
Per-user OAuth in one call. Your Google Cloud Observability MCP server gets session-scoped tokens with zero credentials stored on your infra.
Agent Auth →
Security
Agent Protection
Every Google Cloud Observability tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.
Prompt Injection Defense →
Performance
Max Agent Context. Min Cost.
Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Google Cloud Observability call.
Tools Discovery →What is the Google Cloud Observability MCP Server?
A Google Cloud Observability MCP server lets AI agents read and write Google Cloud Observability data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Google Cloud Observability MCP server ships with 45 pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, and optimized agent context. Connect it from MCP clients like Claude Desktop, Cursor, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.
All Google Cloud Observability MCP Tools and Actions
Every action from Google Cloud Observability's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.
Alert Policys
- Create Alert Policy
Create a new alert policy
- Get Alert Policy
Get an alert policy by resource name
- Update Alert Policy
Update an existing alert policy
- Delete Alert Policy
Delete an alert policy
Dashboards
- Create Dashboard
Create a new dashboard
- List Dashboards
List dashboards in a project
- Get Dashboard
Get a dashboard by resource name
- Update Dashboard
Update an existing dashboard
- Delete Dashboard
Delete a dashboard
Exclusions
- Create Exclusion
Create a new log exclusion
- List Exclusions
List log exclusions in a project
- Get Exclusion
Get a log exclusion by ID
- Update Exclusion
Update an existing log exclusion
- Delete Exclusion
Delete a log exclusion
Log Metrics
- Create Log Metric
Create a new log-based metric
- List Log Metrics
List log-based metrics in a project
- Get Log Metric
Get a log-based metric by ID
- Update Log Metric
Update an existing log-based metric
- Delete Log Metric
Delete a log-based metric
Logs
- List Logs
List the logs in a project
- Delete Log
Delete a log and all its log entries
Metric Descriptors
- List Metric Descriptors
List metric descriptors in a project
- Get Metric Descriptor
Get a metric descriptor by type
Notification Channels
- Create Notification Channel
Create a new notification channel
- List Notification Channels
List notification channels in a project
- Get Notification Channel
Get a notification channel by resource name
- Update Notification Channel
Update an existing notification channel
- Delete Notification Channel
Delete a notification channel
Sinks
- Create Sink
Create a new log sink
- List Sinks
List log sinks in a project
- Get Sink
Get a log sink by ID
- Update Sink
Update an existing log sink
- Delete Sink
Delete a log sink
Uptime Check Configs
- Create Uptime Check Config
Create a new uptime check configuration
- List Uptime Check Configs
List uptime check configurations in a project
- Get Uptime Check Config
Get an uptime check configuration by resource name
- Update Uptime Check Config
Update an existing uptime check configuration
- Delete Uptime Check Config
Delete an uptime check configuration
Other (7)
- List Alert Policies
List alert policies in a project
- List Log Entries
List log entries from Cloud Logging
- List Monitored Resource Descriptors
List monitored resource descriptors in a project
- List Time Series
List time series data for a metric
- Test Auth
Verify Google Cloud Observability credentials
- Write Log Entries
Write log entries to Cloud Logging
- Verify Notification Channel
Verify a notification channel
Set Up Your Google Cloud Observability MCP Server in Minutes
One endpoint. Any framework. Your agent is talking to Google Cloud Observability in under 10 lines of code.
MCP Clients
Agent Frameworks
JSON{
"mcpServers": {
"stackone": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://api.stackone.com/mcp?x-account-id=<account_id>",
"--header",
"Authorization: Basic <YOUR_BASE64_TOKEN>"
]
}
}
}Google Cloud Observability MCP Server Resources
MCP Code Mode: Keeping Tool Responses Out of Agent Context
Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.
11 min
Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery
Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.
10 min
Indirect Prompt Injection Defense for MCP Tools: A Technical Guide
MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.
12 min
Google Cloud Observability MCP Server FAQ
Google Cloud Observability MCP server vs direct API integration — what's the difference?
A Google Cloud Observability MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software — backend code calling Google Cloud Observability. A Google Cloud Observability MCP server is for AI agents — MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI — discovering and calling Google Cloud Observability at runtime. StackOne provides both.
How does Google Cloud Observability authentication work for AI agents?
Google Cloud Observability authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK — you get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own Google Cloud Observability account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via
origin_owner_id.Are Google Cloud Observability MCP tools vulnerable to prompt injection?
Yes — Google Cloud Observability MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content — documents, messages, tickets, records, or free-text fields — is a potential vector. StackOne Defender scans every tool response before it enters the agent's context — regex patterns in ~1ms, then a MiniLM classifier in ~4ms. 88.7% accuracy, CPU-only.
What is the context bloat of a Google Cloud Observability agent and how do I avoid it?
Context bloat happens when Google Cloud Observability tool schemas and API responses eat your Google Cloud Observability agent's memory, preventing it from reasoning effectively. A single Google Cloud Observability query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery and Code Mode reduce context bloat — loading only relevant tools per query and keeping raw responses out of the agent's context.
Can I limit which actions my Google Cloud Observability agent can access?
Yes — you can limit which actions your Google Cloud Observability agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my Google Cloud Observability MCP server?
Yes — you can create custom agent actions for your Google Cloud Observability MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research Google Cloud Observability's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a Google Cloud Observability MCP server?
Skip a Google Cloud Observability MCP server if your integration is purely software-to-software — direct Google Cloud Observability API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call Google Cloud Observability actions at runtime.
What AI frameworks and AI clients does the StackOne Google Cloud Observability MCP server support?
The StackOne Google Cloud Observability MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.
Put your AI agents to work
All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.