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MCP server exposing reusable skills for AI coding agents

Project description

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 — development workflows, code reviews,debugging, etc.— and every team member's AI agent (Claude Code, Cursor, Copilot) can use them automatically.

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)        │
│  └── your skills via --skills-path      │
└─────────────────────────────────────────┘
                    │
                    │ MCP Protocol
                    ▼
┌─────────────────────────────────────────┐
│     AI Coding Agents                    │
│  Claude Code, Cursor, GitHub Copilot    │
└─────────────────────────────────────────┘

How agents use skills:

  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

This mirrors Anthropic's progressive disclosure: metadata first, full content only when needed.

Team workflow:

  1. Team creates a skills repository (manually or via devskills init)
  2. Each developer clones the repo locally
  3. Each developer configures their MCP client to point to the local checkout:
{
  "mcpServers": {
    "devskills": {
      "command": "uvx",
      "args": ["devskills", "--skills-path", "/path/to/team-skills"]
    }
  }
}

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

Add devskills to your agent's MCP config, pointing to your skills:

{
  "mcpServers": {
    "devskills": {
      "command": "uvx",
      "args": ["devskills", "--skills-path", "/path/to/my-team-skills/skills"]
    }
  }
}

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

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

Anthropic Resources:

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