MCP Server - Model Context Protocol

A Rust-native Model Context Protocol (MCP) server for infrastructure automation and AI-assisted DevOps operations.

Source: provisioning/platform/mcp-server/ Status: Proof of Concept Complete

Overview

Replaces the Python implementation with significant performance improvements while maintaining philosophical consistency with the Rust ecosystem approach.

Performance Results

🚀 Rust MCP Server Performance Analysis
==================================================

📋 Server Parsing Performance:
  • Sub-millisecond latency across all operations
  • 0μs average for configuration access

🤖 AI Status Performance:
  • AI Status: 0μs avg (10000 iterations)

💾 Memory Footprint:
  • ServerConfig size: 80 bytes
  • Config size: 272 bytes

✅ Performance Summary:
  • Server parsing: Sub-millisecond latency
  • Configuration access: Microsecond latency
  • Memory efficient: Small struct footprint
  • Zero-copy string operations where possible

Architecture

src/
├── simple_main.rs      # Lightweight MCP server entry point
├── main.rs             # Full MCP server (with SDK integration)
├── lib.rs              # Library interface
├── config.rs           # Configuration management
├── provisioning.rs     # Core provisioning engine
├── tools.rs            # AI-powered parsing tools
├── errors.rs           # Error handling
└── performance_test.rs # Performance benchmarking

Key Features

1. AI-Powered Server Parsing: Natural language to infrastructure config
2. Multi-Provider Support: AWS, UpCloud, Local
3. Configuration Management: TOML-based with environment overrides
4. Error Handling: Comprehensive error types with recovery hints
5. Performance Monitoring: Built-in benchmarking capabilities

Rust vs Python Comparison

Usage

# Build and run
cargo run --bin provisioning-mcp-server --release

# Run with custom config
PROVISIONING_PATH=/path/to/provisioning cargo run --bin provisioning-mcp-server -- --debug

# Run tests
cargo test

# Run benchmarks
cargo run --bin provisioning-mcp-server --release

Configuration

Set via environment variables:

export PROVISIONING_PATH=/path/to/provisioning
export PROVISIONING_AI_PROVIDER=openai
export OPENAI_API_KEY=your-key
export PROVISIONING_DEBUG=true

Integration Benefits

1. Philosophical Consistency: Rust throughout the stack
2. Performance: Sub-millisecond response times
3. Memory Safety: No segfaults, no memory leaks
4. Concurrency: Native async/await support
5. Distribution: Single static binary
6. Cross-compilation: ARM64/x86_64 support

Next Steps

1. Full MCP SDK integration (schema definitions)
2. WebSocket/TCP transport layer
3. Plugin system for extensibility
4. Metrics collection and monitoring
5. Documentation and examples

Related Documentation

• Architecture: MCP Integration