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
- List Available MCP Servers
See which servers are configured in your .mcp.json :
python .claude/tools/mcp-converter/mcp_analyzer.py --list
- Convert a Server
Convert a specific MCP server to a Skill:
python .claude/tools/mcp-converter/mcp_analyzer.py --server <server_name>
- Batch Conversion (Catalog)
Convert multiple servers based on rules:
python .claude/tools/mcp-converter/batch_converter.py
ℹ️ How it Works
-
Introspect: Connects to the running MCP server.
-
Analyze: Estimates token usage of tool schemas.
-
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.