mcp-server

DevOps Community
Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network
Domain
DevOps
Compatible agents
  • Claude Code
  • Cursor
  • Cline
  • Codex
  • Windsurf
  • Gemini CLI
  • +20
Trust score
88 / 100 · community maintained
Author / version / license
@tomevault-io · no license declared
Token usage
Lean
Setup complexity
Manual integration
External API key
Required · Vendor-specific
Operating systems
Docker
Runtime requirements
Node.js · Python · Docker
Permissions
  • Read-only
  • Write / modify
  • Shell exec
  • Env read
Network behavior
External requests
Install commands
26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools,默认拥有全部工具权限。

Output preview mcp-server.preview
---
name: mcp-server
description: This skill should be used when the user asks to "build an MCP server", "create an MCP", "make an…
category: devops
runtime: Node.js / Python / Docker
---

# mcp-server output preview

## PART A: Task fit
- Use case: This skill should be used when the user asks to "build an MCP server", "create an MCP", "make an MCP integration", "wrap an API for Claude", "expose tools to Claude", "develop MCP tools", "implement MCP resources", or discusses building something with the Model Context Protocol. It provides comprehensive guidance for designing, creating, testing, and deploying MCP servers. Use when this capability is needed..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Overview / Phase 1: Discovery / 1. What does it connect to?” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “This skill should be used when the user asks to "build an MCP server", "create an MCP", "make an MCP integration", "wrap an API for Claude", "expose tools to Claude", "develop MCP tools", "implement MCP resources", or discusses building something with the Model Context Protocol. It provides comprehensive guidance for designing, creating, testing, and deploying MCP servers. Use when this capability is needed.”.
- **02** When the source has headings, the agent prioritizes “Overview / Phase 1: Discovery / 1. What does it connect to?” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands, read environment variables; may access external network resources; requires Vendor-specific API keys.

## Running Rules
- read files, write/modify files, run shell commands, read environment variables; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.
Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

  • Core job: This skill should be used when the user asks to "build an MCP server", "create an MCP", "make an MCP integration", "wrap an API…
  • Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
  • Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

  • Structure: The skill is organized around “Overview”, “Phase 1: Discovery”, “1. What does it connect to?”, “2. Who will use it?”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
  • Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
  • Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

  • Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
  • Invocation: Name mcp-server directly; if the source includes slash commands, start with the command and then add task context.
  • Validation: Start small and check whether the result follows “Overview / Phase 1: Discovery / 1. What does it connect to?” before expanding.

Boundaries And Review

  • Dependencies: Prepare Vendor-specific API keys before running a full task.
  • Permissions: Declared permissions include read / write / shell-exec / env-read; ask the agent to state file, command, and rollback boundaries before acting.
  • Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Discussion

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