Provides access to Google Cloud Platform documentation through search and content extraction tools, supporting 20+ GCP products including Compute Engine, Cloud Storage, BigQuery, GKE, Cloud Functions, and more. Enables querying documentation with natural language, fetching specific documentation pages, listing supported products, and accessing REST API references.
Google Cloud Docs MCP Server
An MCP (Model Context Protocol) server that provides AI assistants with access to Google Cloud Platform documentation. This enables Claude and other MCP-compatible assistants to search, fetch, and understand GCP documentation in real-time.
Table of Contents
Features
Free-form Search: Search GCP documentation with natural language queries
Content Extraction: Extract clean markdown content from documentation pages
80+ Topic Mappings: Pre-configured mappings for common GCP topics
Relevance Scoring: Smart ranking of search results by relevance
API Reference: Access REST API documentation for GCP services
20+ GCP Products: Support for major Google Cloud services
How It Works
Query Processing: When Claude receives a GCP-related question, it calls the MCP server tools
Search Strategy: The server uses a multi-step search approach:
Google Search targeting
site:cloud.google.comGoogle Cloud's internal search API (fallback)
80+ pre-configured topic mappings (fallback)
Content Extraction: Uses Cheerio to parse HTML and extract clean markdown
Relevance Scoring: Results are scored and sorted by query relevance
Response: Returns structured JSON with documentation content
Technical Details
Protocol: MCP (Model Context Protocol) over stdio transport
Content Parsing: HTML to Markdown conversion with Cheerio
Search: Combines Google Search scraping with fallback topic mappings
Output Format: Structured JSON with markdown content
Prerequisites
Node.js >= 18.0.0
npm or yarn
Claude Desktop, Claude Code, or other MCP-compatible client
Installation
From Source
Quick Start
Configuration
Claude Desktop
Add to your Claude Desktop config file:
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Claude Code CLI
Usage
Once configured, Claude will automatically use the GCP documentation tools when you ask questions about Google Cloud services.
Example Queries
Direct Tool Usage
If using MCP protocol directly:
Available Tools
1. search_google_cloud_docs
Search GCP documentation with free-form queries. Primary tool for GCP questions.
Parameter | Type | Required | Description |
| string | Yes | Natural language search query |
| string | No | Filter by GCP product (e.g., 'compute', 'storage') |
Example:
2. fetch_google_cloud_doc
Fetch content from a specific documentation page.
Parameter | Type | Required | Description |
| string | Yes | Documentation path after
|
Example:
3. list_google_cloud_products
List all supported GCP products and their documentation paths.
No parameters required.
4. get_api_reference
Get REST API reference for a GCP service.
Parameter | Type | Required | Description |
| string | Yes | Service name (e.g., 'compute', 'storage') |
| string | No | Specific API resource (e.g., 'instances', 'buckets') |
Example:
Supported Topics
The server includes 80+ topic mappings for accurate search results:
Category | Topics |
Storage & Encryption | encrypt, bucket, cmek, kms, customer managed, object storage |
IAM & Security | iam, role, service account, impersonation, workload identity |
Networking | vpc, peering, shared vpc, firewall, load balancer, dns, nat |
Database | cloud sql, high availability, mysql, postgres, replica, failover |
BigQuery | partition, cluster, materialized view, schedule |
GKE | gke, autoscaling, node pool, horizontal pod autoscaler, helm |
Serverless | cloud run, environment variable, cloud function, deploy |
Container | docker, artifact registry, cloud build |
Pub/Sub | pubsub, topic, subscription |
Data Processing | dataflow, dataproc, composer, airflow, spark |
Monitoring | logging, monitoring, metric, alert, dashboard, trace |
Infrastructure | terraform, deployment manager, gcloud |
Supported GCP Products
ID | Name | Description |
| Compute Engine | Virtual machines and infrastructure |
| Cloud Storage | Object storage service |
| BigQuery | Data warehouse and analytics |
| GKE | Managed Kubernetes service |
| Cloud Functions | Serverless compute platform |
| Cloud Run | Serverless containers |
| Pub/Sub | Messaging and event ingestion |
| Cloud SQL | Managed relational databases |
| Firestore | NoSQL document database |
| Cloud Spanner | Globally distributed database |
| Vertex AI | Machine learning platform |
| IAM | Identity and Access Management |
| VPC | Virtual Private Cloud networking |
| Cloud Load Balancing | Global load balancing |
| Cloud Logging | Log management and analysis |
| Cloud Monitoring | Infrastructure monitoring |
Project Structure
Development
Running in Development Mode
Testing the Server
Building
Contributing
Contributions are welcome! Here's how you can help:
Getting Started
Fork the repository
Clone your fork:
git clone https://github.com/yourusername/google-cloud-docs-mcp.gitCreate a feature branch:
git checkout -b feature/your-feature-nameMake your changes
Run tests and build:
npm run buildCommit your changes:
git commit -m "Add your feature"Push to your fork:
git push origin feature/your-feature-nameOpen a Pull Request
Contribution Ideas
Add more topic mappings: Expand the
topicMappingsobject insrc/index.tsSupport more GCP products: Add entries to
GOOGLE_CLOUD_PRODUCTSImprove content extraction: Enhance the Cheerio parsing logic
Add caching: Implement response caching to reduce API calls
Add tests: Write unit tests for search and content extraction
Documentation: Improve README or add usage examples
Code Style
Use TypeScript
Follow existing code patterns
Add comments for complex logic
Test your changes before submitting
Reporting Issues
Found a bug or have a suggestion? Please open an issue with:
Clear description of the problem
Steps to reproduce
Expected vs actual behavior
Your environment (Node.js version, OS)
Acknowledgments
Model Context Protocol - The protocol that enables AI-tool communication
Cheerio - Fast HTML parsing
Google Cloud Documentation - The source of all documentation
License
This project is licensed under the MIT License - see the LICENSE file for details.
Made with love for the GCP and AI community