🧠 .NET MCP Skill Engine

A modular, production-grade framework for building AI-powered skills in .NET using the Model Context Protocol (MCP).

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📌 Overview

The .NET MCP Skill Engine provides a highly extensible, middle-ware based orchestration system for AI agents. It allows you to build "skills" (intelligent tools) once and expose them seamlessly via the Model Context Protocol to any AI consumer (Claude, ChatGPT, etc.).

Key Features:

• Middleware Execution Pipeline: Intercept and augment skill requests with validation, logging, and caching.
• Enterprise-Grade Observability: Native ActivitySource integration for full-stack OpenTelemetry tracing.
• Lean & High Performance: Optimized with LoggerMessage source generators and minimalist dependencies.
• Rules Engine: Flexible policy-based validation for skill invocation.
• Built-in Code Intelligence: A collection of pre-built skills for scaffolding, reviews, and diagnostics.

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🚀 Quick Start

1. Register the Engine

Add the Skill Engine to your service collection in Program.cs:

using SkillEngine.Core;

var builder = WebApplication.CreateBuilder(args);

// Register Core Engine
builder.Services.AddSkillEngine(options => {
    options.MaxParameters = 15;
    options.DeniedTools = ["experimental-tool"];
});

// Register Built-in Skills
builder.Services.AddSkill<ScaffoldSkill>()
                .AddSkill<CodeReviewSkill>()
                .AddSkill<ArchitectureAdvisorSkill>();

// (Optional) Add custom middleware
builder.Services.AddSkillMiddleware<PerformanceMetricsMiddleware>();

2. Invoke a Skill

Inject SkillOrchestrator and execute tools:

public async Task<string> HandleRequest(SkillOrchestrator orchestrator, string toolName)
{
    var request = new SkillRequest { ToolName = toolName };
    var result = await orchestrator.InvokeAsync(request);

    return result.IsSuccess ? result.Content! : $"Error: {result.ErrorMessage}";
}

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🏗️ Architecture

The engine follows Clean Architecture principles, ensuring the core logic is divorced from external protocols like MCP or HTTP.

graph TD
    Consumer[AI Agent / IDE] --> MCP[MCP Endpoints]
    MCP --> Orchestrator[Skill Orchestrator]

    subgraph "Execution Pipeline"
        Orchestrator --> Middleware1[Validation Middleware]
        Middleware1 --> Middleware2[Custom Middleware]
        Middleware2 --> Skill[Target Skill]
    end

    subgraph "Domain Core"
        Skill --> Rules[Rule Engine]
        Skill --> Context[Context Builder]
    end

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Advanced Senior Patterns:

• Observability: Uses System.Diagnostics.Activity to provide detailed spans during skill execution.
• Resilience: Middlewares can be used to implement Retry and Circuit Breaker patterns.
• Decoupling: The ISkillRouter abstracts skill discovery, allowing for dynamic loading of capabilities.

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📂 Project Structure

graph LR
    Core[SkillEngine.Core] --- Tools[SkillEngine.Tools]
    Core --- Mcp[SkillEngine.Mcp]
    Tools --- Mcp

    Core -.-> Examples[examples]
    Tools -.-> Examples
    Mcp -.-> Examples

    Core -.-> Knowledge[knowledge base]

    style Core fill:#f9f,stroke:#333,stroke-width:2px
    style Mcp fill:#bbf,stroke:#333,stroke-width:2px
    style Tools fill:#dfd,stroke:#333,stroke-width:2px

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🛠️ Built-in Skills

Skill	Description
scaffold	Generates Clean Architecture, CQRS, and CRUD boilerplate.
review-code	Expert-level security and performance code review.
explain-error	Diagnostic tool for explaining complex .NET exceptions.
advise-architecture	Tailored advice on patterns (MVC, Hexagonal, etc.).

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🎯 Roadmap

• Middleware Pipeline Architecture
• OpenTelemetry / Tracing support
• Initial Code Intelligence tools
• Multi-format Prompt Templating (Scriban)
• Distributed Caching Middleware
• Auto-discovery of Skill DLLs
• MCP streaming support

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🤝 Contributing

We welcome contributions! Please see our Developer Guide for information on how to add new skills or middlewares.

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📣 Connect

If you're building agentic systems with .NET, I'd love to connect!

• 💼 LinkedIn: Yassine Zakhama
• 📧 Email: zakhamayassine@gmail.com