devskills 0.2.0

MCP server exposing reusable skills for AI coding agents

DevSkills

An MCP server that brings Anthropic's Agent Skills to any MCP-compatible coding agent.

What this enables: Your team creates a shared repository of skills — a skill that reviews PRs with your team's checklist, a skill that scaffolds services following your architecture patterns, a skill that debugs test failures with your stack's quirks in mind — and every team member's AI agent can use them automatically.

• What are Skills?
• The Problem
• How DevSkills Works
• Quick Start
• Usage
• Creating Skills
• Documentation

What are Skills?

Skills are Anthropic's concept for giving AI agents specialized knowledge. Instead of repeating context every conversation, you package instructions, scripts, and references into a folder that agents load on-demand.

Think of skills like onboarding docs for a new hire: "Here's how we do deployments. Here's our code review checklist. Here's the security patterns we follow." Except the new hire is an AI agent.

The key design principle is progressive disclosure — agents see only skill names and descriptions upfront, then load full instructions only when relevant. This means you can have dozens of skills without bloating context.

The Problem

Native Skills support exists only in Claude Code, where skills live in ~/.claude/skills/ or .claude/skills/.

Teams using Cursor, GitHub Copilot, or other AI coding tools can't use Skills and can't share a common skill repository across different tools and maybe even agents running on the server side.

How DevSkills Works

DevSkills runs as an MCP server that exposes your skills to any MCP-compatible agent:

┌─────────────────────────────────────────┐
│     devskills (MCP Server)              │
│  ├── bundled_skills/  (defaults)        │
│  ├── bundled_prompts/ (defaults)        │
│  └── your skills/prompts via --skills-path
└─────────────────────────────────────────┘
          │                    │
          │ MCP Tools          │ MCP Prompts
          │ (model-triggered)  │ (user-triggered)
          ▼                    ▼
┌─────────────────────────────────────────┐
│     AI Coding Agents                    │
│  Claude Code, Cursor, GitHub Copilot    │
└─────────────────────────────────────────┘

Two ways to invoke skills:

Mechanism	Trigger	How it works
MCP Tools	Model decides	Agent calls list_skills() → picks relevant skill → loads instructions
MCP Prompts	User invokes	User triggers /mcp-builder → agent receives prompt → follows skill

Tool-triggered flow (automatic):

1. Discovery — Agent calls list_skills(), sees names and descriptions
2. Selection — Agent decides which skill matches the user's request
3. Loading — Agent calls get_skill(name) to load full instructions
4. Execution — Agent follows the instructions, optionally fetching scripts or references

Prompt-triggered flow (explicit):

1. User invokes — User triggers a prompt (e.g., /skill-creator in Claude Code)
2. Agent receives — Prompt tells agent to use devskills and which skill to load
3. Loading — Agent calls get_skill(name) as directed
4. Execution — Agent follows the instructions

Both flows converge at the same skill instructions—prompts just provide an explicit entry point.

Team workflow:

1. Team creates a skills repository (via devskills init)
2. Each developer clones the repo and configures their MCP client to point to it
3. Same skills, any agent

Quick Start

1. Create a Skills Repository

uvx devskills init my-team-skills
cd my-team-skills
git init && git add . && git commit -m "Initial commit"

2. Configure Your MCP Client

See Setup Guide for agent-specific configuration (Claude Code, Cursor, GitHub Copilot).

Usage

Option 1: Let the agent decide (tools)

Ask your agent naturally, mentioning "use devskills":

Review this PR. Use devskills.

Set up a new API endpoint for user management. Use devskills.

The agent will call list_skills() to discover available skills, pick the relevant one, and follow its instructions.

Option 2: Explicitly invoke a skill (prompts)

Use slash commands to trigger specific skills directly:

/skill-creator

/mcp-builder

The prompt tells the agent exactly which skill to use—no discovery step needed.

Creating Skills

The recommended way to create a skill is using the built-in skill-creator:

I want to create a new skill for code review. Use devskills.

This guides you through creating a skill with the correct structure.

See Creating Skills for the full guide, including skill structure and SKILL.md format.

Documentation

• Setup Guide — Agent-specific MCP configuration
• Creating Skills — Skill structure and format
• Reference — CLI, MCP tools, bundled skills
• Contributing — Development setup

Anthropic Resources:

• Agent Skills Blog Post
• Skills Cookbook