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Agent Skill · 研究检索

create-mcp-server(create MCP server 搜索)

create-mcp-server 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

create-mcp-server 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 26,846。

总安装 3,493周安装 147GitHub Stars 公开资料未说明下载 1,223核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:create-mcp-server(create MCP server 搜索)
来源仓库:https://github.com/arterialist/create-mcp-server
安装命令:
openclaw skills install create-mcp-server
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install create-mcp-server

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

利用 MCPHero 平台通过 mcpheroctl CLI 管理 MCP 服务器实例。支持构建、部署与运维全流程自动化降低中间件接入复杂度。适用于需要对接多数据源或扩展 LLM 上下文能力的系统集成场景。需注册 MCPHero 账号并获取 API 密钥完成身份鉴权流程。

建议先查阅官方文档了解协议规范与资源配额限制详情。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install create-mcp-server;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

create-mcp-server 怎么安装?

在终端执行 openclaw skills install create-mcp-server。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

create-mcp-server 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

create-mcp-server 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

create-mcp-server 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

create-mcp-server 用的人多吗?

公开数据是累计安装 3,493 次,近一周安装 147 次,下载 1,223 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

create-mcp-server 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
create-mcp-server

create MCP server 搜索 · 本页

3,493—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
create-mcp-server
description
|

Create MCP Servers with MCPHero

MCPHero lets agents build their own tools. Instead of burning tokens on API schemas, SQL queries, and output parsing every run, the agent creates a persistent MCP server once and calls it forever. A 50,000-token integration becomes a 50-token tool call.

This skill covers the mcpheroctl CLI workflow for building servers end-to-end.

Production API base URL: https://api.mcphero.app/api


Prerequisites

Before using this skill, the user must have mcpheroctl installed and authenticated.

Install mcpheroctl

# via Homebrew (macOS/Linux)
brew install arterialist/mcpheroctl/mcpheroctl

# via uv (cross-platform)
uv tool install mcpheroctl

Authenticate

  1. Log in to the MCPHero Dashboard.
  2. Go to Settings → Organization → Developers.
  3. Click Create API key and copy the token.
  4. Run:
mcpheroctl auth login --token <YOUR_ORG_TOKEN>

Verify

mcpheroctl auth status

The Wizard Pipeline

The CLI follows this linear flow. After any async step, poll wizard state and check processing_status == "idle" before proceeding.

1. create-session          → Returns server_id (save it, needed everywhere)
2. conversation (loop)     → Gather requirements; stop when is_ready: true
3. start                   → Transition to tool suggestion (async → poll)
4. list-tools              → Review AI-suggested tools
5. refine-tools (optional) → Iterate on tools until satisfied (async → poll)
6. submit-tools            → Confirm selection (deletes unselected tools)
7. (auto env var suggest)  → Triggered automatically after submit-tools (async → poll)
8. list-env-vars           → Review suggested env vars
9. refine-env-vars (opt.)  → Iterate on env vars (async → poll)
10. submit-env-vars        → Provide actual values (call even if list is empty — backend needs it to transition)
11. set-auth               → Generate bearer token for the server
12. generate-code          → Trigger code generation (async → poll)
13. deploy                 → Deploy to MCPHero runtime → returns server_url + bearer_token

Always call submit-env-vars, even when list-env-vars returns []. The backend requires this step to transition to the next state. With no env vars, just call it with no --var flags.


State Machine

The setup_status field in wizard state tells you where you are:

gathering_requirements     → User is chatting about requirements
tools_generating           → LLM is generating tool suggestions (async, poll)
tools_selection            → Tools ready for review/selection
env_vars_generating        → LLM is generating env var suggestions (async, poll)
env_vars_setup             → Env vars ready for review/submission
auth_selection             → Ready for auth setup
code_generating            → LLM is generating code (async, poll)
code_gen                   → Code ready for review
deployment_selection       → Ready to deploy
ready                      → Server deployed and live

States ending in _generating are transient — poll until they transition. The processing_status field is the reliable check: "idle" means done, "processing" means wait, "error" means check processing_error.


Full Wizard Example

Always use --json for scriptable output. Without it, human-friendly messages go to stderr and can confuse parsing.

# 1. Create session
mcpheroctl wizard create-session --json
# → {"server_id": "abc-123-..."}
SERVER_ID="abc-123-..."

# 2. Describe requirements (iterate until is_ready: true)
mcpheroctl wizard conversation $SERVER_ID --json \
  -m "I have a PostgreSQL database with customers and orders tables. I need tools to find customers by name, fetch orders for a customer, and get last hour's orders."
# Repeat with follow-up messages until output shows: "is_ready": true

# 3. Start tool suggestion (async)
mcpheroctl wizard start $SERVER_ID --json
# → {"status": "processing"}

# Poll until processing is done (check processing_status, not setup_status)
until mcpheroctl wizard state $SERVER_ID --json 2>/dev/null | \
  python3 -c "import sys,json; exit(0 if json.load(sys.stdin).get('processing_status')=='idle' else 1)"; do
  sleep 3
done

# 4. Review tools (state should be "tools_selection")
mcpheroctl wizard list-tools $SERVER_ID --json

# 5. Refine if needed (async → poll again)
mcpheroctl wizard refine-tools $SERVER_ID --json \
  -f "Add error handling for missing customers. Rename get_customers_orders to get_orders_by_customer."

# 6. Submit selected tool IDs
mcpheroctl wizard submit-tools $SERVER_ID --json \
  --tool-id <tool-uuid-1> \
  --tool-id <tool-uuid-2> \
  --tool-id <tool-uuid-3>

# 7. Wait for env var suggestion (auto-triggered, state becomes "env_vars_setup")
until mcpheroctl wizard state $SERVER_ID --json 2>/dev/null | \
  python3 -c "import sys,json; exit(0 if json.load(sys.stdin).get('processing_status')=='idle' else 1)"; do
  sleep 3
done

# 8. Review env vars
mcpheroctl wizard list-env-vars $SERVER_ID --json

# 9. Submit env var values (format: VAR_UUID=VALUE)
# ALWAYS call this even if list-env-vars returned [] — backend needs it to transition.
# With env vars:
mcpheroctl wizard submit-env-vars $SERVER_ID --json \
  --var "<env-var-uuid-1>=localhost" \
  --var "<env-var-uuid-2>=5432"
# Without env vars (empty list):
mcpheroctl wizard submit-env-vars $SERVER_ID --json

# 10. Set authentication
mcpheroctl wizard set-auth $SERVER_ID --json
# → {"bearer_token": "..."}  ← SAVE THIS

# 11. Generate code (async → poll)
mcpheroctl wizard generate-code $SERVER_ID --json
until mcpheroctl wizard state $SERVER_ID --json 2>/dev/null | \
  python3 -c "import sys,json; exit(0 if json.load(sys.stdin).get('processing_status')=='idle' else 1)"; do
  sleep 3
done

# 12. Deploy
mcpheroctl wizard deploy $SERVER_ID --json
# → {"server_url": "/mcp/<server-id>/mcp", "bearer_token": "...", "step": "complete"}

IMPORTANT: deploy returns a relative server_url like /mcp/<id>/mcp. Prepend the base domain to get the full URL:

https://api.mcphero.app/mcp/<server-id>/mcp

Server Management

mcpheroctl server list --json [CUSTOMER_ID]  # List all servers
mcpheroctl server get SERVER_ID --json       # Get server details + status
mcpheroctl server update SERVER_ID           # Update name/description
mcpheroctl server delete SERVER_ID --yes     # Delete (irreversible)
mcpheroctl server api-key SERVER_ID --json   # Retrieve bearer token

Polling Pattern

The reliable way to poll is to check processing_status, not setup_status:

until mcpheroctl wizard state $SERVER_ID --json 2>/dev/null | \
  python3 -c "import sys,json; exit(0 if json.load(sys.stdin).get('processing_status')=='idle' else 1)"; do
  sleep 3
done

Connecting a Deployed Server to MCP Clients

After deploy, construct the full server URL:

https://api.mcphero.app{server_url}

Claude Desktop config

{
  "mcpServers": {
    "my-server": {
      "url": "https://api.mcphero.app/mcp/<server-id>/mcp",
      "headers": {
        "Authorization": "Bearer <bearer_token>"
      }
    }
  }
}

Config file locations:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/claude/claude_desktop_config.json

Key Tips

Free tier: Max 5 tools per server. wizard_submit_tools will error if more are selected.

server_id is everything: Save the UUID returned from create_session. Every subsequent call needs it.

Env var format in CLI: --var "UUID=VALUE" — the UUID is the env var's id from list-env-vars, not its name.

Empty env vars: Even if list-env-vars returns [], you must still call submit-env-vars (with no vars) so the backend transitions to the next state.

Regenerate without redeploy: After using wizard_regenerate_tool_code, the code change takes effect immediately for already-deployed servers (the server auto-remounts).

Always use --json: In CLI commands, --json sends structured data to stdout. Without it, human-friendly messages go to stderr and can break piping/parsing.


Exit Codes

CodeMeaning
0Success
1General failure
2Usage/argument error
3Resource not found
4Not authenticated
5Conflict

平台分布

OpenClaw

74.93%
按下载量换算916

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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