Templates

Skill bjornslib/mcp-to-uber-skills-converter/skills/mcp-to-skill-converter/templates

Claude Code plugin that converts MCP servers to Claude Skills with progressive disclosure. Reduces context usage by 90%+.

Install

npx -y skills add bjornslib/mcp-to-uber-skills-converter --skill templates

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Registry of MCP-derived skills with progressive disclosure. Use when asked about "github", "assistant-ui", "MCP tools", or any converted MCP server. Provides 90%+ context savings compared to native MCP loading.

SKILL.md

2.7 KB, as published. Nobody here has run it

MCP Skills Registry

Central directory for all MCP-derived skills. Each sub-skill wraps an MCP server with progressive disclosure.

Available Skills

Skill	Tools	Trigger Keywords

See index.json for the machine-readable list.

⚠️ These Are Skill Wrappers, NOT Native MCP Tools

You CANNOT call mcp__shadcn__*, mcp__github__*, etc. directly - those don't exist. These skills wrap MCP servers via a central executor.py.

Usage

Step 1: Read the skill's SKILL.md (from project root):

cat .claude/skills/mcp-skills/<skill-name>/SKILL.md

# Example: shadcn skill
cat .claude/skills/mcp-skills/shadcn/SKILL.md

Step 2: Use the central executor.py (from project root):

# List available skills
python .claude/skills/mcp-skills/executor.py --skills

# List tools in a skill
python .claude/skills/mcp-skills/executor.py --skill github --list

# Get tool schema
python .claude/skills/mcp-skills/executor.py --skill github --describe create_issue

# Call a tool
python .claude/skills/mcp-skills/executor.py --skill github --call '{"tool": "create_issue", "arguments": {...}}'

Context Efficiency

Scenario	Native MCP (all servers)	This Registry	Savings
Idle	40-100k tokens	~150 tokens	99%+
Using 1 skill	40-100k tokens	~5k tokens	90%+
After execution	40-100k tokens	~150 tokens	99%+

How It Works

Registry loads first - This file (~150 tokens)
User requests a tool - e.g., "create a GitHub PR"
Sub-skill loads - Only the relevant skill's SKILL.md (~4k tokens)
Executor runs - External process, 0 context tokens
Result returned - Context drops back to registry only

Adding New Skills

Use the mcp-to-skill-converter skill:

cd .claude/skills/mcp-to-skill-converter
python mcp_to_skill.py --name <server-name>
# Outputs to .claude/skills/mcp-skills/<server-name>/

Skill Structure

Each sub-skill contains:

.claude/skills/mcp-skills/<skill-name>/
├── SKILL.md           # Tool documentation
├── executor.py        # Async MCP client (legacy, use central executor)
├── mcp-config.json    # Server config
└── package.json       # Dependencies

This registry enables progressive disclosure of MCP servers as Claude Skills.