MCP vs Agent Skills: Understanding the Two Approaches to AI Tool Extension

"Should I use MCP or Agent Skills?" is a common question when extending AI tools.

Both are open standards championed by Anthropic, but they solve fundamentally different problems. The short answer: they're complementary, not competing. Using them together often produces the best results.

This article explains the differences between MCP and Agent Skills, and when to choose each.

What is MCP: Connecting AI to External Systems

MCP (Model Context Protocol) is a standard protocol for connecting AI applications to external systems.

Think of it Like USB-C

The easiest way to understand MCP is to think of it like a USB-C port. Just as USB-C provides a universal way to connect smartphones to peripherals, MCP provides a universal way to connect AI applications to databases, APIs, file systems, and more.

What MCP Enables

With MCP, AI can access external resources like:

• Local files: Documents and code on your machine
• Databases: Query and update data with SQL
• External APIs: Google Calendar, Notion, Slack, and other services
• Custom tools: Functions you've built yourself

MCP Architecture

MCP uses a client-server structure:

CopyAI Application (Claude Code, ChatGPT, etc.)
       ↓
   MCP Client
       ↓
   MCP Servers (multiple possible)
   ├─ File Server (local file access)
   ├─ Git Server (repository operations)
   ├─ DB Server (database queries)
   └─ Custom Server (your own logic)

What are Agent Skills: Packaged Knowledge and Workflows

Agent Skills teach AI "how to do things." By writing procedures and knowledge in a SKILL.md file, AI can apply that expertise to tasks.

Simple File-Based Structure

An Agent Skill is essentially a Markdown file called SKILL.md:

Copy---
name: Code Review
description: Review PR code changes
---

## Steps

1. Check changed files
2. Evaluate code quality, security, and performance
3. Point out issues with specific suggestions

No network connection needed—just place it locally and it works.

The Core Difference: "What to Access" vs "How to Execute"

The fundamental difference in one sentence:

• MCP: Gives AI access to "what" it needs
• Agent Skills: Teaches AI "how" to do something

Comparison Table

Concrete Examples

Posting a message to Slack

• MCP approach: Set up a Slack MCP server, AI directly calls Slack API
• Agent Skills approach: Define "Slack posting procedure" as a skill, AI guides you through the steps

MCP enables direct action; Agent Skills standardize the process.

Improving code review efficiency

• MCP approach: Use GitHub MCP server to fetch PR diffs
• Agent Skills approach: Define "code review criteria" as a skill

In this case, combining MCP to fetch data and Agent Skills to standardize review methods works best.

When to Use Which

Choose MCP When:

• You need real-time external data
• You want to directly interact with databases or APIs
• You need to integrate multiple services

Choose Agent Skills When:

• You want to standardize workflows across a team
• You'll reuse specific procedures repeatedly
• You need to work without network connectivity

Combine Both When:

The most powerful workflows combine both approaches:

1. MCP fetches external data (GitHub PR diffs, database records, etc.)
2. Agent Skills define processing methods (review criteria, analysis procedures, etc.)

Caveats and Current Limitations

MCP Considerations

• Server setup required (technical barrier)
• Security configuration is critical (credential management)
• Need to keep up with external service changes

Agent Skills Considerations

• Cannot directly access external systems
• Skill quality varies (community-dependent)
• Not 100% compatible across all tools

Common to Both

Both technologies are still evolving. OpenAI officially adopted MCP in March 2025, and the ecosystem is expanding rapidly—but specification changes are still possible.

Summary

MCP and Agent Skills solve different problems:

• MCP: Connecting AI to external systems ("what to access")
• Agent Skills: Expertise and workflows ("how to execute")

Rather than choosing one, use both as needed for the most practical approach.

To start with Agent Skills, browse the Skills list for ones that interest you. For MCP, the official documentation is a good starting point.

Related Articles

• What Are Agent Skills? - Start with the basics
• AI Coding Tools Comparison 2026 - Claude Code, Codex CLI, Cursor differences
• How to Set Up Skills in Claude Code - Get started
• Agent Skills Trends January 2026 - Ecosystem status