MCP-to-Skill Converter

Installation

The skill invokes

.claude/tools/integrations/mcp-converter/batch_converter.py

. Requirements:

• Python 3.10+: python.org or

  winget install Python.Python.3.12

  (Windows),

  brew install python@3.12

  (macOS).
• pip: Usually included with Python; verify with

  pip --version

  .
• Dependencies: From the repo root, install deps for the integration (e.g. PyYAML if required):

  pip install pyyaml
  

  Run from project root; the script uses

  .claude/tools/integrations/mcp-converter/

  (catalog:

  mcp-catalog.yaml

  ).

Cheat Sheet & Best Practices

MCP design: Single responsibility per server; bounded toolsets; contracts first (strict I/O schemas); stateless by default; additive changes; security (identity, auth, audit). Prefer stdio for local, Streamable HTTP for remote; use a gateway for multi-tenant/centralized policy.

Conversion: Introspect server; estimate token usage of tool schemas; generate skill with progressive disclosure. Test converted skills before relying on them. Use catalog + batch_converter for rules-driven conversion.

Hacks: Focus on high-token or high-value servers first. Keep generated SKILL.md and wrappers in version control. Use

mcp-catalog.yaml

to mark

keep_as_mcp

or auto-convert thresholds.

Certifications & Training

MCP: MCP Best Practices, modelcontextprotocol.info. Skill data: Single responsibility, bounded tools, contracts first, stateless; stdio vs HTTP; gateway pattern; introspect → generate skill.

Hooks & Workflows

Suggested hooks: Post–MCP config change: optional batch_converter run to refresh skills. Use with evolution-orchestrator (add mcp-converter to secondary) when creating skills from MCP servers.

Workflows: Use with evolution-orchestrator. Flow: list servers → convert server or batch → test converted skill. See

creators/skill-creator-workflow.yaml

; mcp-converter feeds skill-creator input.

🚀 Usage

1. List Available MCP Servers

See which servers are configured in your

.mcp.json

:

python .claude/tools/mcp-converter/mcp_analyzer.py --list

2. Convert a Server

Convert a specific MCP server to a Skill:

python .claude/tools/mcp-converter/mcp_analyzer.py --server <server_name>

3. Batch Conversion (Catalog)

Convert multiple servers based on rules:

python .claude/tools/mcp-converter/batch_converter.py

ℹ️ How it Works

1. Introspect: Connects to the running MCP server.
2. Analyze: Estimates token usage of tool schemas.
3. Generate: Creates a

   SKILL.md

   wrapper that creates dynamic tool calls only when needed.

🔧 Dependencies

Requires

mcp

python package:

pip install mcp

Memory Protocol (MANDATORY)

Before starting: Read

.claude/context/memory/learnings.md

After completing:

• New pattern ->

  .claude/context/memory/learnings.md

• Issue found ->

  .claude/context/memory/issues.md

• Decision made ->

  .claude/context/memory/decisions.md

ASSUME INTERRUPTION: If it's not in memory, it didn't happen.