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How to Choose Between MCP Servers and Claude Skills

I built an MCP server for git operations. Took me three hours. Then I realized Claude already knows git commands better than I do. I had over-engineered a simple problem.

That’s when I learned the hard rule: match the tool to the complexity.

The Problem: Two Ways to Extend Claude

When you want Claude to do more than chat, you have two options:

  1. MCP Servers: External programs that Claude connects to via a protocol
  2. Claude Skills: Markdown files with instructions Claude follows

Both work. Both have tradeoffs. I kept picking the wrong one.

At first, I thought MCP was “more professional.” So I built MCP servers for everything. Git operations. File management. Running tests. Each one took hours to set up properly.

Then I discovered Skills. A 10-line markdown file replaced my 200-line git MCP server. Same functionality. Fraction of the effort.

The Key Difference

Here’s the mental model that finally clicked:

MCP Servers: Claude doesn’t know the tool. The MCP server acts as a translator, teaching Claude how to use it.

Skills: Claude already knows the tool. The skill just reminds Claude how you want it used.

This distinction matters because it tells you which to use.

When to Use Claude Skills

Use Skills when Claude already understands the tool. This includes:

  • git: Claude knows git flags better than most developers
  • npm/yarn/pnpm: Standard package managers with clear commands
  • docker: Well-documented CLI that Claude has memorized
  • File operations: Read, write, move, organize

For these, a Skill is just structured instructions. Here’s one I use:

Simple git commit skill
---
name: git-commit
description: Create git commits with conventional format
---
Create a git commit with:
1. Conventional commit message format
2. Proper author attribution
3. Only staged changes
4. Reference any related issues

That’s it. No protocol. No server. No deployment. Claude reads this and follows the instructions.

What Makes Skills Work

Skills work because Claude has already seen thousands of git commands during training. It knows:

  • What git commit -m means
  • How to stage files with git add
  • How to check status with git status
  • The conventional commit format

The skill just guides Claude to apply that knowledge consistently.

When to Use MCP Servers

Use MCP servers when the tool has complexity that requires translation:

  • 100+ operations with interdependent parameters
  • Domain expertise needed to compose operations correctly
  • Claude doesn’t know the tool’s patterns and gotchas

Examples:

ToolWhy MCPOperations
AWS SDK1000+ operations, complex IAM relationshipsHigh
Kubernetes APIHundreds of resource types, dependenciesHigh
Database clientsTransaction handling, connection poolingMedium-High
Enterprise APIsCustom protocols, auth schemesVaries

For these, Claude can’t just “figure it out.” The MCP server provides:

  1. Schema validation: Ensures parameters are correct
  2. Domain knowledge: Guides Claude on which operations work together
  3. Error handling: Translates cryptic API errors into actionable guidance

A Real MCP Server Structure

When you need MCP, you’re building something substantial:

MCP server for complex API
import { Server } from '@modelcontextprotocol/sdk/server';
const server = new Server({
name: 'database-integration',
version: '1.0.0'
});
// Handles complex operations:
// - Connection pooling
// - Transaction management
// - Query optimization
// - Schema migrations
// - Relationship traversal

This is not a 10-line markdown file. It’s real code with real complexity.

The Decision Framework

I use a simple heuristic from a Reddit discussion:

“If the tool already has a good CLI, skip MCP and let Claude use the CLI directly. MCP only earns its complexity when the tool has hundreds of operations with parameter relationships that require domain knowledge to compose correctly.”

Here’s my decision flow:

MCP vs Skills decision flow
Start with question: Does Claude know this tool?
YES → Use a Skill (5-10 minutes)
└── Write instructions in markdown
└── Claude applies existing knowledge
NO → Ask: Are there 100+ operations with dependencies?
YES → Use MCP (2-4 hours minimum)
└── Build server with schema validation
└── Include domain knowledge
└── Handle complex error cases
NO → Try Skill first
└── May need MCP later if complexity grows

Common Mistakes I Made

Mistake 1: Building MCP for Simple Things

I built an MCP server for file operations. Read, write, move files. Total overkill.

A simple skill would have worked:

File organizer skill
---
name: file-organizer
description: Organize files by extension into folders
---
Organize the specified directory:
1. Scan all files
2. Create folders by extension (images/, documents/, code/)
3. Move files to appropriate folders
4. Report summary of changes

Claude knows file operations. It just needed guidance on what I wanted.

Mistake 2: Ignoring YAGNI

I kept adding MCP servers “just in case.” Building infrastructure for problems I might have someday.

The result: maintenance burden, context bloat, slower responses.

Now I follow a different rule: Start with Skills. Graduate to MCP only when proven necessary.

Mistake 3: Under-engineering Complex Integrations

I tried to use a Skill for AWS VPC creation. The prompt was a disaster:

Trying to handle AWS with a skill (WRONG)
"Use AWS CLI to create VPC with subnets, route tables,
security groups, and proper CIDR block allocation..."

Claude got confused. CIDR blocks overlapped. Route tables had wrong associations. Security groups didn’t attach properly.

This needed an MCP server with real domain knowledge:

  • Validating CIDR block relationships
  • Understanding subnet-to-AZ mapping
  • Orchestrating resource creation order
  • Handling IAM permissions

Some problems need structure, not just instructions.

The Hybrid Approach

My current setup uses both:

Task TypeToolReason
git operationsSkillClaude knows git
npm/yarnSkillClaude knows package managers
docker commandsSkillWell-documented CLI
AWS operationsMCPComplex, needs validation
Database queriesMCPConnection handling, transactions
File organizationSkillSimple operations

I also use a routing skill to dispatch to the right tool:

Command routing skill
---
name: do
description: Intelligent routing to skills, agents, and pipelines
---
Parse user intent from: $ARGUMENTS
Route to appropriate handler:
- File operations → file-organizer skill
- Database queries → database-mcp server
- Code review → code-reviewer agent
- Testing → tdd-guide agent

This lets me use /do organize downloads folder without remembering which tool handles what.

Time Investment Comparison

The biggest practical difference is development time:

AspectSkillsMCP Servers
Initial setup5-10 minutes2-4 hours minimum
File formatMarkdownTypeScript/Python/etc
DeploymentDrop in folderBuild, deploy, debug
MaintenanceEdit text fileCode changes, dependencies
SharingCopy fileDeploy infrastructure

This isn’t to say MCP is bad. MCP is powerful. But power comes with cost.

Development Velocity Impact

I track how long things take:

  • Skill for git workflow: 8 minutes from idea to working

  • MCP server for git: 3 hours, and I abandoned it when I realized Claude already knew git

  • Skill for simple file processing: 5 minutes

  • MCP server for file processing: Would have taken 2+ hours

  • Skill for AWS VPC creation: Didn’t work, wasted 30 minutes trying

  • MCP server for AWS: 4 hours but actually works correctly

The pattern: Skills are fast to try, MCP is slow but handles complexity.

What I Recommend

  1. Default to Skills: Start here for 80% of use cases
  2. Watch for complexity: If a skill grows to 500+ lines, reconsider
  3. Evaluate MCP need: Does the tool have 100+ operations with relationships?
  4. Use hybrid routing: A /do skill that dispatches to appropriate tools
  5. Remember YAGNI: Don’t build MCP servers for problems you don’t have yet

Getting Started

If you’re new to extending Claude:

  1. Try a Skill first for any tool
  2. If Claude struggles, check if it’s a complexity issue
  3. Only build MCP when Skills fundamentally can’t handle the task
  4. Keep Skills small and focused
  5. Name Skills clearly so you remember what they do

The goal isn’t to use the “right” technology. The goal is to solve problems efficiently.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!

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