A production-ready Model Context Protocol (MCP) server for Google Cloud Dataproc operations. Provides intelligent defaults, comprehensive tooling, and seamless integration with Roo (VS Code) for big data workflows.
npm install @dipseth/dataproc-mcp-server









A production-ready Model Context Protocol (MCP) server for Google Cloud Dataproc operations with intelligent parameter injection, enterprise-grade security, and comprehensive tooling. Designed for seamless integration with Roo (VS Code).
Add this to your Roo MCP settings:
``json`
{
"mcpServers": {
"dataproc": {
"command": "npx",
"args": ["@dipseth/dataproc-mcp-server@latest"],
"env": {
"LOG_LEVEL": "info"
}
}
}
}
`json`
{
"mcpServers": {
"dataproc": {
"command": "npx",
"args": ["@dipseth/dataproc-mcp-server@latest"],
"env": {
"LOG_LEVEL": "info",
"DATAPROC_CONFIG_PATH": "/path/to/your/config.json"
}
}
}
}
`bashInstall globally
npm install -g @dipseth/dataproc-mcp-server
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1. Install the package:
`bash
npm install -g @dipseth/dataproc-mcp-server@latest
`2. Run the setup:
`bash
dataproc-mcp --setup
`3. Configure authentication:
`bash
# Edit the generated config file
nano config/server.json
`4. Start the server:
`bash
dataproc-mcp
`$3
β
PRODUCTION-READY: Full Claude.ai Integration with HTTPS Tunneling & OAuth
The Dataproc MCP Server now provides complete Claude.ai web app compatibility with a working solution that includes all 22 MCP tools!
#### π Working Solution (Tested & Verified)
Terminal 1 - Start MCP Server:
`bash
DATAPROC_CONFIG_PATH=config/github-oauth-server.json npm start -- --http --oauth --port 8080
`Terminal 2 - Start Cloudflare Tunnel:
`bash
cloudflared tunnel --url https://localhost:8443 --origin-server-name localhost --no-tls-verify
`Result: Claude.ai can see and use all tools successfully! π
#### Key Features:
- β
Complete Tool Access - All 22 MCP tools available in Claude.ai
- β
HTTPS Tunneling - Cloudflare tunnel for secure external access
- β
OAuth Authentication - GitHub OAuth for secure authentication
- β
Trusted Certificates - No browser warnings or connection issues
- β
WebSocket Support - Full WebSocket compatibility with Claude.ai
- β
Production Ready - Tested and verified working solution
#### Quick Setup:
1. Setup GitHub OAuth (5 minutes)
2. Generate SSL certificates:
npm run ssl:generate
3. Start services (2 terminals as shown above)
4. Connect Claude.ai to your tunnel URLdocs/claude-ai-integration.md for detailed setup instructions, troubleshooting, and advanced features.docs/trusted-certificates.md for SSL certificate configuration.β¨ Features
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- 22 Production-Ready MCP Tools - Complete Dataproc management suite
- π§ Knowledge Base Semantic Search - Natural language queries with optional Qdrant integration
- π Response Optimization - 60-96% token reduction with Qdrant storage
- π Generic Type Conversion System - Automatic, type-safe data transformations
- 60-80% Parameter Reduction - Intelligent default injection
- Multi-Environment Support - Dev/staging/production configurations
- Service Account Impersonation - Enterprise authentication
- Real-time Job Monitoring - Comprehensive status tracking$3
- 96.2% Token Reduction - list_clusters: 7,651 β 292 tokens
- Automatic Qdrant Storage - Full data preserved and searchable
- Resource URI Access - dataproc://responses/clusters/list/abc123
- Graceful Fallback - Works without Qdrant, falls back to full responses
- 9.95ms Processing - Lightning-fast optimization with <1MB memory usage$3
- 75% Code Reduction - Eliminates manual conversion logic across services
- Type-Safe Transformations - Automatic field detection and mapping
- Intelligent Compression - Field-level compression with configurable thresholds
- 0.50ms Conversion Times - Lightning-fast processing with 100% compression ratios
- Zero-Configuration - Works automatically with existing TypeScript types
- Backward Compatible - Seamless integration with existing functionality$3
- Input Validation - Zod schemas for all 16 tools
- Rate Limiting - Configurable abuse prevention
- Credential Management - Secure handling and rotation
- Audit Logging - Comprehensive security event tracking
- Threat Detection - Injection attack prevention$3
- 90%+ Test Coverage - Comprehensive test suite
- Performance Monitoring - Configurable thresholds
- Multi-Environment Testing - Cross-platform validation
- Automated Quality Gates - CI/CD integration
- Security Scanning - Vulnerability management$3
- 5-Minute Setup - Quick start guide
- Interactive Documentation - HTML docs with examples
- Comprehensive Examples - Multi-environment configs
- Troubleshooting Guides - Common issues and solutions
- IDE Integration - TypeScript supportπ οΈ Complete MCP Tools Suite (22 Tools)
> π Enhanced with Generic Type Conversion: All tools now benefit from automatic, type-safe data transformations with intelligent compression and field mapping.
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| Tool | Description | Smart Defaults | Key Features |
|------|-------------|----------------|--------------|
| start_dataproc_cluster | Create and start new clusters | β
80% fewer params | Profile-based, auto-config |
| create_cluster_from_yaml | Create from YAML configuration | β
Project/region injection | Template-driven setup |
| create_cluster_from_profile | Create using predefined profiles | β
85% fewer params | 8 built-in profiles |
| list_clusters | List all clusters with filtering | β
No params needed | Semantic queries, pagination |
| list_tracked_clusters | List MCP-created clusters | β
Profile filtering | Creation tracking |
| get_cluster | Get detailed cluster information | β
75% fewer params | Semantic data extraction |
| delete_cluster | Delete existing clusters | β
Project/region defaults | Safe deletion |
| get_zeppelin_url | Get Zeppelin notebook URL | β
Auto-discovery | Web interface access |$3
| Tool | Description | Smart Defaults | Key Features |
|------|-------------|----------------|--------------|
| submit_hive_query | Submit Hive queries to clusters | β
70% fewer params | Async support, timeouts |
| submit_dataproc_job | Submit Spark/PySpark/Presto jobs | β
75% fewer params | Multi-engine support, Local file staging |
| cancel_dataproc_job | Cancel running or pending jobs | β
JobID only needed | Emergency cancellation, cost control |
| get_job_status | Get job execution status | β
JobID only needed | Real-time monitoring |
| get_job_results | Get job outputs and results | β
Auto-pagination | Result formatting |
| get_query_status | Get Hive query status | β
Minimal params | Query tracking |
| get_query_results | Get Hive query results | β
Smart pagination | Enhanced async support |$3
| Tool | Description | Smart Defaults | Key Features |
|------|-------------|----------------|--------------|
| list_profiles | List available cluster profiles | β
Category filtering | 8 production profiles |
| get_profile | Get detailed profile configuration | β
Profile ID only | Template access |
| query_cluster_data | Query stored cluster data | β
Natural language | Semantic search |$3
| Tool | Description | Smart Defaults | Key Features |
|------|-------------|----------------|--------------|
| check_active_jobs | Quick status of all active jobs | β
No params needed | Multi-project view |
| get_cluster_insights | Comprehensive cluster analytics | β
Auto-discovery | Machine types, components |
| get_job_analytics | Job performance analytics | β
Success rates | Error patterns, metrics |
| query_knowledge | Query comprehensive knowledge base | β
Natural language | Clusters, jobs, errors |$3
- π§ Semantic Search: Natural language queries with Qdrant integration
- β‘ Smart Defaults: 60-80% parameter reduction through intelligent injection
- π Response Optimization: 96% token reduction with full data preservation
- π Async Support: Non-blocking job submission and monitoring
- π·οΈ Profile System: 8 production-ready cluster templates
- π Analytics: Comprehensive insights and performance trackingπ Configuration
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The server supports a project-based configuration format:
`yaml
profiles/@analytics-workloads.yaml
my-company-analytics-prod-1234:
region: us-central1
tags:
- DataProc
- analytics
- production
labels:
service: analytics-service
owner: data-team
environment: production
cluster_config:
# ... cluster configuration
`$3
1. Service Account Impersonation (Recommended)
2. Direct Service Account Key
3. Application Default Credentials
4. Hybrid Authentication with fallbacks
π Documentation
- Quick Start Guide - Get started in 5 minutes
- Knowledge Base Semantic Search - Natural language queries and setup
- Generic Type Conversion System - Architectural design and implementation
- Generic Converter Migration Guide - Migration from manual conversions
- API Reference - Complete tool documentation
- Configuration Examples - Real-world configurations
- Security Guide - Best practices and compliance
- Installation Guide - Detailed setup instructions
π§ MCP Client Integration
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`json
{
"mcpServers": {
"dataproc": {
"command": "npx",
"args": ["@dataproc/mcp-server"],
"env": {
"LOG_LEVEL": "info"
}
}
}
}
`$3
`json
{
"mcpServers": {
"dataproc-server": {
"command": "npx",
"args": ["@dataproc/mcp-server"],
"disabled": false,
"alwaysAllow": [
"list_clusters",
"get_cluster",
"list_profiles"
]
}
}
}
`ποΈ Architecture
`
βββββββββββββββββββ ββββββββββββββββββββ βββββββββββββββββββ
β MCP Client ββββββ Dataproc MCP ββββββ Google Cloud β
β (Claude/Roo) β β Server β β Dataproc β
βββββββββββββββββββ ββββββββββββββββββββ βββββββββββββββββββ
β
ββββββββ΄βββββββ
β Features β
βββββββββββββββ€
β β’ Security β
β β’ Profiles β
β β’ Validationβ
β β’ Monitoringβ
β β’ Generic β
β Converter β
βββββββββββββββ
`$3
`
βββββββββββββββββββ ββββββββββββββββββββ βββββββββββββββββββ
β Source Types ββββββ Generic Converter ββββββ Qdrant Payloads β
β β’ ClusterData β β System β β β’ Compressed β
β β’ QueryResults β β β β β’ Type-Safe β
β β’ JobData β β ββββββββββββββββ β β β’ Optimized β
βββββββββββββββββββ β βField Analyzerβ β βββββββββββββββββββ
β βTransformationβ β
β βEngine β β
β βCompression β β
β βService β β
β ββββββββββββββββ β
ββββββββββββββββββββ
`π¦ Performance
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- Schema Validation: ~2ms (target: <5ms) β
- Parameter Injection: ~1ms (target: <2ms) β
- Generic Type Conversion: ~0.50ms (target: <2ms) β
- Credential Validation: ~25ms (target: <50ms) β
- MCP Tool Call: ~50ms (target: <100ms) β
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- Schema Validation: ~2000 ops/sec β
- Parameter Injection: ~5000 ops/sec β
- Generic Type Conversion: ~2000 ops/sec β
- Credential Validation: ~200 ops/sec β
- MCP Tool Call: ~100 ops/sec β
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- Field-Level Compression: Up to 100% compression ratios β
- Memory Optimization: 30-60% reduction in memory usage β
- Type Safety: Zero runtime type errors with automatic validation β
π§ͺ Testing
`bash
Run all tests
npm testRun specific test suites
npm run test:unit
npm run test:integration
npm run test:performanceRun with coverage
npm run test:coverage
`π€ Contributing
We welcome contributions! Please see our Contributing Guide for details.
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`bash
Clone the repository
git clone https://github.com/dipseth/dataproc-mcp.git
cd dataproc-mcpInstall dependencies
npm installBuild the project
npm run buildRun tests
npm testStart development server
npm run dev
``This project is licensed under the MIT License - see the LICENSE file for details.
- GitHub Issues: Report bugs and request features
- Documentation: Complete documentation
- NPM Package: Package information
- Model Context Protocol - The protocol that makes this possible
- Google Cloud Dataproc - The service we're integrating with
- Qdrant - High-performance vector database powering our semantic search and knowledge indexing
- TypeScript - For type safety and developer experience
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Made with β€οΈ for the MCP and Google Cloud communities