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Skills vs MCP Servers: When to Use What

Skills vs MCP: two approaches to extend your AI capabilities. Discover the differences, advantages of each, and how to choose the right tool.

AAdmin
February 26, 20265 min read

Skills vs MCP Servers: The Comparison Guide

In the AI-assisted ecosystem, two approaches dominate for extending your assistant's capabilities: skills (SKILL.md files) and MCP servers (Model Context Protocol). Understanding the difference between skills vs MCP is crucial for choosing the right solution for your needs.

What Is a Skill?

A skill is a Markdown file containing instructions to guide AI behavior. It's structured knowledge — not executable code.

# My Skill
## Instructions
1. Analyze the current file
2. Identify functions without tests
3. Generate missing tests

Key Characteristics

  • Format: Pure Markdown, human-readable
  • Execution: The AI interprets and executes instructions
  • Installation: Copy a file into a directory
  • Portability: Works on Claude Code, Cursor, Windsurf, Copilot
  • Maintenance: Zero dependencies, zero infrastructure

What Is an MCP Server?

An MCP server is a program running in the background that exposes tools the AI can call. It's executable code with structured APIs.

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"]
    }
  }
}

Key Characteristics

  • Format: Code (TypeScript, Python, etc.)
  • Execution: Independent process with API
  • Installation: npm install, JSON configuration
  • Portability: Depends on MCP support in the tool
  • Maintenance: Dependencies, updates, potential bugs

Detailed Comparison: Skills vs MCP

| Criteria | Skills | MCP Servers | |----------|--------|-------------| | Complexity | Low | Medium to high | | Creation time | 10 minutes | Hours to days | | External API access | No (through AI) | Yes (native) | | Database access | No | Yes | | Portability | Excellent | Variable | | Maintenance | Near zero | Ongoing | | Power | AI guidance | Programmatic tools | | Learning curve | Very low | Medium |

When to Use a Skill

Choose a skill when:

1. The Task Is Text-Based

Generating code, writing documentation, refactoring — anything that manipulates text is the ideal playground for skills.

2. You Want Portability

The same SKILL.md works on Claude Code, Cursor, and Windsurf. No adaptation needed.

3. The Team Isn't Technical

Writing a skill requires zero programming knowledge. A project manager can create a spec-writing skill.

4. Creation Speed Matters

10 minutes for a working skill vs several hours for an MCP server.

Good Skill Examples

  • UI component generation
  • Automated code review
  • Commit conventions
  • Documentation templates
  • Refactoring workflows

When to Use an MCP Server

Choose an MCP server when:

1. You Need External API Access

Interacting with GitHub, Jira, Slack, a database — anything requiring network calls.

2. Data Is Dynamic

Listing open tickets, retrieving real-time metrics, querying a database — skills can't do this natively.

3. Security Is Critical

MCP servers handle authentication, tokens, and permissions securely on the server side.

4. The Operation Is Complex

Image manipulation, binary file parsing, heavy computation — anything beyond text processing.

Good MCP Server Examples

  • GitHub integration (PRs, issues)
  • Database access (PostgreSQL, Redis)
  • Monitoring tools (Datadog, Sentry)
  • Cloud file management (S3, GCS)
  • Communication (Slack, email)

The Hybrid Approach: Best of Both Worlds

The most effective strategy combines both. A skill orchestrates the workflow while MCP servers provide the data.

# Skill: Prepare a Release
## Instructions
1. Use the GitHub MCP to list merged PRs
2. Generate the changelog from PR titles
3. Create the version tag
4. Use the Slack MCP to notify the team

In this example, the skill defines the what and the how, while MCP servers provide the with what.

Decision Tree

To choose between skills vs MCP, ask yourself:

  1. Does the task require network access? -> MCP
  2. Is the task purely text-based? -> Skill
  3. Do you need real-time data? -> MCP
  4. Do you want cross-tool sharing? -> Skill
  5. Do you have 10 minutes? -> Skill. Several hours? -> MCP if needed.

Conclusion

The skills vs MCP debate isn't a binary choice. Skills excel at guiding AI through text-based tasks with instant setup. MCP servers are indispensable when AI needs to interact with the outside world. Use both intelligently to maximize your AI assistant's power.

Discover our ready-to-use skills and our AI agents to get started today.

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