#1 trial priority · playbooks / Workflow Automation
mcp-builder skill by icartsh/icartsh_plugin
- Fit
- 66 / 100
- Trust
- Needs review
- Setup
- MCP ready
- Before run
- 1 check
Top risk
No community evaluationAgentStaffer users have not submitted a review yet.
Full readiness snapshotCandidate summary and risk context stay available here.
LLM이 잘 설계된 도구를 통해 외부 서비스와 상호작용할 수 있게 해주는 고품질 MCP (Model Context Protocol) 서버를 만들기 위한 가이드입니다. Python (FastMCP) 또는 Node/TypeScript (MCP SDK)를 사용하여 외부 API나 서비스를 통합하는 MCP 서버를 구축할 때 사용하세요.
Top risk
No community evaluation: AgentStaffer users have not submitted a review yet.
Trial task Run a dry-run workflow trial
- Input
- Connect the workflow to mock inputs and ask it to produce a trace without touching production systems.
- Expected output
- A step-by-step run log with inputs, outputs, failures, and rollback notes.
Permissions & setup
- Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
- MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
- Clear Install path reviewed
- Hold Trust evidence reviewed
Guardrails
- Install asks for production credentials or broad write access.
- Source or package cannot be verified from profile evidence.
Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.