Afrexai Mcp Engineering

# MCP Engineering — Complete Model Context Protocol System

Build, integrate, secure, and scale MCP servers and clients. From first server to production multi-tool architecture.

## When to Use

- Building an MCP server (any language)
- Integrating MCP tools into an AI agent
- Debugging MCP connection/auth issues
- Designing multi-server architectures
- Securing MCP endpoints for production
- Evaluating which MCP servers to use

---

## Phase 1: MCP Fundamentals

### What MCP Is
Model Context Protocol = standardized way for AI agents to call external tools. Think of it as "USB for AI" — one protocol, any tool.

### Architecture
```
Agent (Client) ←→ MCP Transport ←→ MCP Server ←→ External Service
                   (stdio/HTTP)      (your code)    (API, DB, file system)
```

### Core Concepts
| Concept | What It Does | Example |
|---------|-------------|---------|
| **Server** | Exposes tools, resources, prompts | A server wrapping the GitHub API |
| **Client** | Discovers and calls server capabilities | OpenClaw, Claude Desktop, Cursor |
| **Tool** | A callable function with typed params | `create_issue(title, body, labels)` |
| **Resource** | Read-only data the agent can access | `file://workspace/config.json` |
| **Prompt** | Reusable prompt templates | `summarize_pr(pr_url)` |
| **Transport** | How client↔server communicate | stdio (local) or HTTP+SSE (remote) |

### Transport Decision
| Factor | stdio | HTTP/SSE | Streamable HTTP |
|--------|-------|----------|-----------------|
| Setup complexity | Low | Medium | Medium |
| Multi-client | No | Yes | Yes |
| Remote access | No | Yes | Yes |
| Streaming | Via stdio | SSE | Native |
| Auth needed | No (local) | Yes | Yes |
| Best for | Local dev, single agent | Production, shared | Modern production |

**Rule:** Start with stdio for development. Move to HTTP for production or multi-agent.

---

## Phase 2: Building Your First MCP Server

### Server Brief YAML
```yaml
server_name: "[service]-mcp"
description: "[Wh...

# AfrexAI MCP Engineering

Complete Model Context Protocol system — build, integrate, secure, and scale MCP servers for AI agents.

## Install

```bash
clawhub install afrexai-mcp-engineering
```

## What You Get

11-phase MCP engineering methodology:

1. **Fundamentals** — Architecture, concepts, transport selection
2. **Build** — TypeScript + Python server templates with tool design rules
3. **Production** — HTTP transport, auth patterns, production checklist
4. **Integration** — OpenClaw/Claude Desktop config, multi-server architecture
5. **Testing** — Test pyramid, per-tool checklist, MCP Inspector
6. **Patterns** — API wrapper, database, file system, workflow, aggregator
7. **Security** — Threat model, hardening checklist, dangerous patterns to avoid
8. **Debugging** — Common issues table, debug workflow, logging template
9. **Evaluation** — Score existing servers before using them (0-30 rubric)
10. **Architecture** — Single agent, gateway, agent-per-domain patterns + tool count limits
11. **Publishing** — Package structure, README template, npm publishing

Plus: 100-point quality rubric, 10 common mistakes, 12 natural language commands.

## Quick Start

Ask your agent:
- "Build an MCP server for [any API]"
- "Secure my MCP server for production"
- "Debug why my MCP tool isn't appearing"
- "How should I architect 5 MCP servers?"

## Why This Over Other MCP Skills

Other MCP skills are either CLI wrappers for specific tools or single-framework guides. This is the complete engineering methodology — from first tool to production multi-server architecture. Zero dependencies.

## ⚡ Level Up

Want production-ready AI agent configurations for your industry?

**AfrexAI Context Packs ($47)** — Complete agent setups for SaaS, Fintech, Healthcare, Legal, Construction, Ecommerce, Real Estate, Recruitment, Manufacturing, and Professional Services.

👉 [Browse Context Packs](https://afrexai-cto.github.io/context-packs/)

## 🔗 More Free Skills by AfrexAI

- `afrexai-agent-e...