Distribution and sharing

Skills make your MCP integration more complete. As users compare connectors, those with skills offer a faster path to value, giving you an edge over MCP-only alternatives.

Current distribution model (January 2026)

How individual users get skills

1. Download the skill folder
2. Zip the folder (if needed)
3. Upload to Claude.ai via Settings > Capabilities > Skills
4. Or place in Claude Code skills directory

Organization-level skills

• Admins can deploy skills workspace-wide (shipped December 18, 2025)
• Automatic updates
• Centralized management

An open standard

We've published Agent Skills (opens in new tab) as an open standard. Like MCP, we believe skills should be portable across tools and platforms - the same skill should work whether you're using Claude or other AI platforms. That said, some skills are designed to take full advantage of a specific platform's capabilities; authors can note this in the skill's compatibility field. We've been collaborating with members of the ecosystem on the standard, and we're excited by early adoption.

Using skills via API

For programmatic use cases - such as building applications, agents, or automated workflows that leverage skills - the API provides direct control over skill management and execution.

Key capabilities

• /v1/skills endpoint for listing and managing skills
• Add skills to Messages API requests via the container.skills parameter
• Version control and management through the Claude Console
• Works with the Claude Agent SDK for building custom agents

When to use skills via the API vs. Claude.ai

Note: Skills in the API require the Code Execution Tool beta, which provides the secure environment skills need to run.

For implementation details, see:

• Skills API Quickstart (opens in new tab)
• Create Custom skills (opens in new tab)
• Skills in the Agent SDK (opens in new tab)

Recommended approach today

Start by hosting your skill on GitHub with a public repo, clear README (for human visitors — this is separate from your skill folder, which should not contain a README.md), and example usage with screenshots. Then add a section to your MCP documentation that links to the skill, explains why using both together is valuable, and provides a quick-start guide.

1. Host on GitHub
   • Public repo for open-source skills
   • Clear README with installation instructions
   • Example usage and screenshots
2. Document in your MCP repo
   • Link to skills from MCP documentation
   • Explain the value of using both together
   • Provide quick-start guide
3. Create an installation guide

## Installing the [Your Service] skill

1. Download the skill:
   - Clone repo: `git clone https://github.com/yourcompany/skills`
   - Or download ZIP from Releases

2. Install in Claude:
   - Open Claude.ai > Settings > skills
   - Click "Upload skill"
   - Select the skill folder (zipped)

3. Enable the skill:
   - Toggle on the [Your Service] skill
   - Ensure your MCP server is connected

4. Test:
   - Ask Claude: "Set up a new project in [Your Service]"

Positioning your skill

How you describe your skill determines whether users understand its value and actually try it. When writing about your skill—in your README, documentation, or marketing - keep these principles in mind.

Focus on outcomes, not features

✅ Good:

"The ProjectHub skill enables teams to set up complete project workspaces in seconds — including pages, databases, and templates — instead of spending 30 minutes on manual setup."

❌ Bad:

"The ProjectHub skill is a folder containing YAML frontmatter and Markdown instructions that calls our MCP server tools."

Highlight the MCP + skills story

"Our MCP server gives Claude access to your Linear projects. Our skills teach Claude your team's sprint planning workflow. Together, they enable AI-powered project management."