In the fourth installment of our series “My First Communication with MCP and .NET,” we delve into constructing a sophisticated hybrid architecture. This approach intelligently merges the unparalleled efficiency and strong typing of gRPC for inter-service communication with the flexibility and native real-time capabilities of WebSocket for web and mobile clients. The result is a robust, scalable, and highly performant MCP ecosystem, perfectly poised for modern enterprise applications.

The evolution of modern enterprise systems frequently presents a compelling challenge: how to leverage the distinct advantages of different communication protocols. While gRPC shines in backend microservice communication, offering low latency and schema enforcement, WebSocket is indispensable for interactive web and mobile interfaces that demand real-time data updates. This article provides a comprehensive guide to building a cohesive system that seamlessly integrates both, featuring smart routing, protocol translation, and unified monitoring.

Hybrid Architecture: The Synergy of Two Worlds

Our proposed architecture is designed for optimal performance and flexibility. It centralizes control and data flow, allowing various client types to interact with the system using their preferred protocol, without compromising internal service efficiency.

Architectural Overview:

Imagine an API Gateway acting as a smart orchestrator, directing incoming requests to the appropriate protocol endpoint. Beneath this, a Protocol Adapter layer intelligently translates messages, ensuring that the core business logic, housed within a Unified MCP Kernel, remains protocol-agnostic. An Event Bus, powered by Redis, facilitates seamless event synchronization across all components, while a comprehensive Observability Layer provides an end-to-end view of system health and performance.

Key Components:

1. Protocol Orchestrator (API Gateway / BFF): This component is the entry point, responsible for intelligently routing client requests to either the gRPC or WebSocket endpoint based on context.
2. Protocol Adapter Layer: Acts as a translator, converting messages between gRPC and WebSocket formats, enabling seamless communication between different parts of the system regardless of their native protocol.
3. Unified MCP Kernel: The heart of the application, this layer processes all commands, abstracting away the underlying communication protocol from the core business logic.
4. Event Bus (Redis): Utilizes Redis Pub/Sub for highly efficient, cross-protocol event synchronization, ensuring all connected services and clients receive critical updates in real-time.
5. Observability Layer: A unified system for tracing, logging, and metrics, providing deep insights into the hybrid architecture’s performance and behavior.

Implementing the Hybrid Architecture in .NET

This section outlines the practical implementation steps using C# and various .NET technologies.

1. Project Structure: A modular project layout (MCPPipeline.Hybrid) ensures clear separation of concerns, with dedicated projects for contracts, core logic, gRPC services, WebSocket services, gateway, and adapters.

2. Shared Contracts: Defines common data models (e.g., MCPCommand, MCPResponse, MCPEvent) and enums (ProtocolType, ResponseStatus) to ensure type safety and consistency across the entire system, regardless of the protocol in use.

3. Unified MCP Kernel: The IMCPKernelService and MCPKernelService encapsulate the core business logic, processing commands (ExecuteCommandAsync) and handling data streams (StreamCommandAsync) independently of whether they originated from a gRPC or WebSocket client. It integrates with the Event Bus to publish lifecycle events.

4. Event Bus with Redis: An IEventBus interface and its RedisEventBus implementation use StackExchange.Redis to enable efficient publish-subscribe messaging, ensuring real-time event propagation and synchronization across distributed services and connected clients.

5. Protocol Adapter: The IProtocolAdapter and ProtocolAdapter classes provide the crucial translation logic, converting incoming gRPC requests into the unified MCPCommand format for the kernel, and transforming kernel responses back into gRPC-specific messages. Similar logic applies for WebSocket messages within the SignalR hub.

6. gRPC Service Endpoint: The MCPGrpcServiceImpl exposes gRPC endpoints, leveraging the IProtocolAdapter to convert gRPC requests to internal commands and kernel responses back to gRPC responses. It also supports server-side streaming for efficient data transfer.

7. WebSocket Service Endpoint (SignalR Hub): The MCPHub extends SignalR’s Hub to manage WebSocket connections. It receives and sends messages, enriching incoming commands with WebSocket context before passing them to the unified kernel, and then broadcasts responses or streams data back to clients. CORS is configured to allow broad client access.

8. API Gateway with YARP: The YARP (Yet Another Reverse Proxy) powered API Gateway acts as the intelligent traffic controller. Configured via appsettings.json, it routes requests based on their path to either the gRPC or WebSocket backend services, providing a single, unified entry point for clients.

9. Unified Client: A UnifiedMCPClient demonstrates how a single client-side abstraction can interact with both gRPC and WebSocket endpoints. It intelligently switches between gRPC (using GrpcChannel) and WebSocket (using HubConnectionBuilder) based on configuration, simplifying client development for hybrid architectures.

Unified Observability

A critical aspect of any distributed system is robust observability. Our hybrid architecture integrates OpenTelemetry for comprehensive tracing and metrics.

• OpenTelemetry Configuration: Services are configured with AddMCPObservability, enabling tracing instrumentation for ASP.NET Core, gRPC clients, and custom sources (MCPPipeline.Core, .GrpcService, .WebSocketService). Traces are exported via OTLP to a Jaeger collector. Metrics are collected using ASP.NET Core and Runtime instrumentation, along with custom meters, and exported to Prometheus and OTLP.

• Custom Metrics: The MCPMetrics class utilizes System.Diagnostics.Metrics to track specific application metrics such as mcp.commands.processed (total commands), mcp.command.duration (processing time histogram), mcp.commands.errors (error count), and mcp.connections.active (active connections per protocol). These metrics provide fine-grained insights into the system’s operational health.

Dashboard with Grafana

To visualize and analyze the collected metrics and traces, Prometheus and Grafana are employed.

• Prometheus Configuration: A prometheus.yml file is set up to scrape metrics endpoints from the gRPC service, WebSocket service, and API Gateway at regular intervals.

• Grafana Dashboard JSON: A pre-defined Grafana dashboard (JSON provided in the original content) offers immediate insights into key performance indicators, including commands processed by protocol, average command latency, active connections, and error rates, enabling proactive monitoring and troubleshooting.

Integration Tests

Thorough integration testing is essential to validate the seamless operation of a hybrid system.

• Hybrid Testing: Integration tests (e.g., HybridProtocolTests using Xunit) are designed to verify that the same command can be processed correctly via both gRPC and WebSocket. These tests also cover scenarios like concurrent requests from both protocols and ensure that events are broadcast effectively across the different communication channels.

Performance Test

To understand the performance characteristics of each protocol within the hybrid setup, benchmarks are conducted using BenchmarkDotNet.

• BenchmarkDotNet: The ProtocolBenchmarks class compares the performance of sending commands and streaming data over gRPC versus WebSocket. The expected results typically show gRPC offering lower latency and memory allocation for single requests, while WebSocket provides efficient, long-lived bidirectional communication, especially beneficial for streaming scenarios.

Protocol Decision: When to Use Each

Choosing the right protocol is crucial for optimal application design.

• Decision Matrix: A ProtocolSelector class (and an accompanying ClientContext record) demonstrates a contextual decision-making process. Factors like client type (web browser, internal service, mobile app), requirement for long-lived streams, latency sensitivity, and need for broadcast capabilities guide the choice between gRPC and WebSocket.

• Comparative Table:

  Scenario	gRPC	WebSocket	Recommendation
  Backend → Backend API	✅ Ideal	⚠️ Overhead	gRPC
  Web Application → Backend	❌ Limited	✅ Native	WebSocket
  Mobile App → Backend	✅ Excellent	✅ Bom	gRPC (better performance)
  Real-time Dashboard	⚠️ Polling	✅ Native Push	WebSocket
  Multi-user Chat	❌ Not ideal	✅ Perfect	WebSocket
  Data Analysis	✅ High Performance	⚠️ Slower	gRPC
  AI Streaming	✅ Eficiente	✅ Funcional	Both (context-dependent)

Security in a Hybrid Environment

Securing a hybrid architecture requires a unified approach to authentication and authorization.

• Unified Authentication: Leverages JWT Bearer authentication, configured to support tokens sent via standard HTTP headers (for gRPC) and query strings (common for WebSocket connections in SignalR). A gRPC AuthenticationInterceptor ensures that all gRPC calls are authenticated, enforcing consistent security policies across protocols.

• Rate Limiting Unificado: Employs ASP.NET Core’s rate limiting features with distinct policies for “grpc” (fixed window) and “websocket” (sliding window) traffic. This allows for granular control over request rates for different protocols, protecting backend services from overload and abuse.

Docker Compose for a Complete Local Environment

To simplify local development, testing, and demonstration, a docker-compose.yml file orchestrates the entire hybrid ecosystem.

• Docker Compose Configuration: Sets up essential infrastructure like Redis (for the event bus), Jaeger (for distributed tracing), Prometheus (for metrics collection), and Grafana (for visualization). It also builds and runs the gRPC, WebSocket, and API Gateway services, linking them appropriately and exposing necessary ports.

Scalability Strategies

The architecture is designed with scalability in mind, using containerization and orchestration.

• Kubernetes Deployment: An example k8s/mcp-deployment.yaml demonstrates how individual services (like the gRPC service) can be deployed and scaled within a Kubernetes cluster, ensuring high availability and elastic scaling based on demand. ConfigMap can be used to manage environment-specific configurations.

Conclusion and Next Steps

This fourth part of our series has successfully established a robust hybrid architecture, demonstrating the powerful combination of gRPC and WebSocket. We’ve shown how to achieve:

• High Performance and Type Safety: For internal service-to-service communication using gRPC.
• Real-time Interactivity and Flexibility: For diverse client applications via WebSocket.
• Unified Core Logic: Through a protocol-agnostic MCP Kernel.
• Centralized Monitoring: With comprehensive observability and Grafana dashboards.
• Robust Security: Via unified authentication and rate limiting.

Future Series Parts:

• Part 5: Deep dive into advanced messaging with Kafka or RabbitMQ for truly asynchronous, high-throughput scenarios.
• Part 6: Implementing resilience patterns like Circuit Breakers and Retries using Polly.
• Part 7: Strategies for multi-cloud deployment and continuous integration/continuous delivery (CI/CD) with GitHub Actions.

Explore the Code:
For complete examples and automation scripts, refer to the MCPPipeline.Hybrid GitHub repository.

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Connect With Me:

If you’re interested in modern .NET development, architecture, C#, observability, DevOps, or interoperability, let’s connect:

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