GCP MCP
The GCP MCP server enables AI assistants like Claude to interact with your Google Cloud Platform environment using natural language.
Query and manage GCP resources: List and modify projects, clusters, SQL instances, storage buckets, Cloud Functions, Cloud Run services, and BigQuery datasets/tables
Execute custom code: Run TypeScript code using Google Cloud Client Libraries for advanced GCP interactions
Billing insights: Retrieve billing information, cost forecasts, and budget details
Project selection: Choose specific GCP projects for targeted operations
Multi-region support: Work seamlessly across different GCP regions
Secure operations: Uses your local GCP credentials without exposing them
Log management: Fetch and filter Cloud Logging entries for debugging
Error handling: Automatically retry failed operations for improved reliability
Enables querying and management of Google Cloud Platform resources including Compute Engine, Cloud Storage, Cloud Functions, Cloud Run, BigQuery, Cloud SQL, GKE, Cloud Logging, Cloud Billing and Resource Manager using natural language.
Provides tools for listing and managing Google Kubernetes Engine (GKE) clusters across different regions.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@GCP MCP list all Cloud Storage buckets in my current project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
GCP MCP
A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with your Google Cloud Platform environment. This allows for natural language querying and management of your GCP resources during conversations.

Features
🔍 Query and modify GCP resources using natural language
☁️ Support for multiple GCP projects
🌐 Multi-region support
🔐 Secure credential handling (no credentials are exposed to external services)
🏃♂️ Local execution with your GCP credentials
🔄 Automatic retries for improved reliability
Related MCP server: Kubectl MCP Tool
Prerequisites
Node.js
Claude Desktop/Cursor/Windsurf
GCP credentials configured locally (application default credentials)
Installation
Clone the repository:
git clone https://github.com/eniayomi/gcp-mcp
cd gcp-mcpInstall dependencies:
npm installConfiguration
Claude Desktop
Open Claude desktop app and go to Settings -> Developer -> Edit Config
Add the following entry to your
claude_desktop_config.json:
via npm:
{
"mcpServers": {
"gcp": {
"command": "sh",
"args": ["-c", "npx -y gcp-mcp"]
}
}
}If you installed from source:
{
"mcpServers": {
"gcp": {
"command": "npm",
"args": [
"--silent",
"--prefix",
"/path/to/gcp-mcp",
"start"
]
}
}
}Replace /path/to/gcp-mcp with the actual path to your project directory if using source installation.
Cursor
Open Cursor and go to Settings (⌘,)
Navigate to AI -> Model Context Protocol
Add a new MCP configuration:
{
"gcp": {
"command": "npx -y gcp-mcp"
}
}Windsurf
Open
~/.windsurf/config.json(create if it doesn't exist)Add the MCP configuration:
{
"mcpServers": {
"gcp": {
"command": "npx -y gcp-mcp"
}
}
}GCP Setup
Set up GCP credentials:
Set up application default credentials using
gcloud auth application-default login
Refresh your AI assistant (Claude Desktop/Cursor/Windsurf)
Usage
Start by selecting a project or asking questions like:
"List all GCP projects I have access to"
"Show me all Cloud SQL instances in project X"
"What's my current billing status?"
"Show me the logs from my Cloud Run services"
"List all GKE clusters in us-central1"
"Show me all Cloud Storage buckets in project X"
"What Cloud Functions are deployed in us-central1?"
"List all Cloud Run services"
"Show me BigQuery datasets and tables"
Available Tools
run-gcp-code: Execute GCP API calls using TypeScript codelist-projects: List all accessible GCP projectsselect-project: Select a GCP project for subsequent operationsget-billing-info: Get billing information for the current projectget-cost-forecast: Get cost forecast for the current projectget-billing-budget: Get billing budgets for the current projectlist-gke-clusters: List all GKE clusters in the current projectlist-sql-instances: List all Cloud SQL instances in the current projectget-logs: Get Cloud Logging entries for the current project
Example Interactions
List available projects:
List all GCP projects I have access toSelect a project:
Use project my-project-idCheck billing status:
What's my current billing status?View logs:
Show me the last 10 log entries from my projectSupported Services
Google Compute Engine
Cloud Storage
Cloud Functions
Cloud Run
BigQuery
Cloud SQL
Google Kubernetes Engine (GKE)
Cloud Logging
Cloud Billing
Resource Manager
More coming soon...
Troubleshooting
To see logs:
tail -n 50 -f ~/Library/Logs/Claude/mcp-server-gcp.logCommon issues:
Authentication errors: Ensure you've run
gcloud auth application-default loginPermission errors: Check IAM roles for your account
API errors: Verify that required APIs are enabled in your project
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT
Available Tools
9 toolsget-billing-budgetC
Get billing budgets for the current project
Inputs: projectId.
get-billing-infoC
Get billing information for the current project
Inputs: projectId.
get-cost-forecastB
Get cost forecast for the current project
Inputs: months, projectId.
get-logsB
Get Cloud Logging entries for the current project
Inputs: filter, pageSize.
list-gke-clustersB
List all GKE clusters in the current project
Inputs: location.
list-projectsA
List all GCP projects accessible with current credentials
Inputs: no named parameters.
list-sql-instancesB
List all Cloud SQL instances in the current project
Inputs: no named parameters.
run-gcp-codeD
Run GCP code
Inputs: code (required), reasoning (required), region, projectId.
select-projectB
Selects GCP project to use for subsequent interactions
Inputs: projectId (required), region.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 9 tools
Tools are mostly distinct: billing-related tools (budget, info, forecast) are clearly separate, and list/select tools for different resources are unambiguous. The only potential confusion is 'run-gcp-code' which is vague but still distinct from other tools.
All tool names follow a consistent verb-noun pattern with hyphens (e.g., get-billing-budget, list-gke-clusters, select-project). The naming convention is uniform and predictable.
The server has 9 tools, which is an appropriate size for a focused GCP management server. It covers several key areas without being overwhelming.
The tool surface is limited to reading and listing operations for select GCP services (billing, logs, GKE, SQL, projects). Missing CRUD operations for resources, compute, storage, IAM, and other common GCP tasks. The vague 'run-gcp-code' tool does not compensate for these gaps.
Maintenance
Related MCP Connectors
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