技能详情(站内镜像,无评论)
许可证:MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本:v1.0.0
统计:⭐ 0 · 21 · 0 current installs · 0 all-time installs
⭐ 0
安装量(当前) 0
🛡 VirusTotal :良性 · OpenClaw :良性
Package:arterialist/meta-mcp-creator
安全扫描(ClawHub)
- VirusTotal :良性
- OpenClaw :良性
OpenClaw 评估
The skill's instructions, requirements, and behavior are internally consistent with its stated purpose (creating and deploying MCP servers via api.mcphero.app) and it does not request unrelated credentials or install arbitrary code.
目的
Name/description match the instructions: the SKILL.md tells the agent how to register the Meta‑MCP endpoint, run the wizard pipeline, and deploy servers at api.mcphero.app. It does not request unrelated binaries, OS access, or unrelated cloud credentials. Note: the skill explicitly enables publishing servers that can wrap internal APIs and accept secrets (env vars / bearer tokens) — this is consistent with its purpose but raises operational se…
说明范围
The runtime instructions are narrowly scoped to using the Meta‑MCP wizard: creating sessions, polling async steps, submitting tool/env var selections, generating auth tokens, and editing your MCP client config (paths for Claude Desktop are specified). The instructions do require supplying env var values and placing Authorization headers into client config (i.e., secrets may be provided to the remote service). The skill does not instruct the ag…
安装机制
Instruction-only skill with no install spec and no code files — lowest installation risk. Nothing is downloaded or written by the skill itself.
证书
The skill declares no required environment variables or credentials. The wizard flow legitimately asks the user (or agent acting for the user) to submit environment variable values and bearer tokens for the servers it creates; these are proportional to the declared goal of deploying hosted MCP servers. Users should be aware those submitted secrets go to api.mcphero.app and will be stored/used by that service.
持久
always:false and default autonomous invocation settings; the skill does not request permanent inclusion or modify other skills or system-wide configs. It only suggests edits to the user's MCP client config to register the created server, which is expected for this functionality.
综合结论
This skill appears coherent and does what it says: it helps you create and deploy MCP servers via the remote endpoint at api.mcphero.app. Before using it, verify you trust api.mcphero.app (there's no homepage or source listed), and be cautious about submitting production secrets or internal endpoints. Specifically: (1) confirm the security/privacy/retention policies of mcphero.app; (2) prefer scoped or short‑lived credentials when providing be…
安装(复制给龙虾 AI)
将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Create MCP Servers using Meta-MCP」。简介:Use the MCPHero Meta-MCP server inside AI clients (Claude Desktop, Cursor, etc.…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/arterialist/meta-mcp-creator/SKILL.md
(来源:yingzhi8.cn 技能库)
SKILL.md
---
name: meta-mcp-wizard
description: |
Use the MCPHero Meta-MCP server inside AI clients (Claude Desktop, Cursor, etc.) to create, deploy, and manage MCP servers through the wizard pipeline. Use this skill when the user wants to connect the Meta-MCP server, build MCP servers interactively via MCP tools, or asks about the meta-mcp endpoint at api.mcphero.app.
---
# Meta-MCP Wizard
The [MCPHero](https://mcphero.app) **Meta-MCP server** lets agents build persistent tools without leaving their MCP client. Instead of re-explaining an API or re-generating SQL on every run, the agent creates a hosted MCP server once and calls it forever — saving 95-99% on token usage for recurring tasks.
Connect it to Claude Desktop, Cursor, or any MCP client, and your agent can build, deploy, and register new MCP servers on the fly.
**Meta-MCP endpoint:** `https://api.mcphero.app/mcp/meta/mcp`
---
## Setup
Add the Meta-MCP server to your MCP client config:
### Claude Desktop
```json
// ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"mcphero": {
"url": "https://api.mcphero.app/mcp/meta/mcp"
}
}
}
```
Config file locations:
- **macOS:** `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Windows:** `%APPDATA%Claudeclaude_desktop_config.json`
- **Linux:** `~/.config/claude/claude_desktop_config.json`
### Cursor and other MCP clients
Add the same URL `https://api.mcphero.app/mcp/meta/mcp` to your client's MCP server config. The client handles OAuth 2.1 authentication automatically on first use.
---
## Available Tools
The Meta-MCP server exposes these tools:
| Tool | Purpose |
|------|---------|
| `wizard_create_session` | Start session; returns `server_id` |
| `wizard_chat` | Send requirement message; returns `is_ready` flag |
| `wizard_start` | Transition to tool suggestion (async) |
| `wizard_list_tools` | List suggested tools with IDs, code, params |
| `wizard_refine_tools` | Refine with feedback (async) |
| `wizard_submit_tools` | Confirm selection by tool UUID list |
| `wizard_suggest_env_vars` | Re-trigger env var suggestion (async) |
| `wizard_list_env_vars` | List env vars with IDs and descriptions |
| `wizard_refine_env_vars` | Refine env vars with feedback (async) |
| `wizard_submit_env_vars` | Submit values as `{uuid: value}` dict |
| `wizard_set_auth` | Generate bearer token |
| `wizard_generate_code` | Trigger code gen (async) |
| `wizard_regenerate_tool_code` | Regenerate single tool code (sync) |
| `wizard_deploy` | Deploy and get server URL |
| `wizard_state` | Poll current state — use after all async steps |
---
## Async vs Sync Tools
**Async** (trigger then poll `wizard_state`): `wizard_start`, `wizard_refine_tools`, `wizard_suggest_env_vars`, `wizard_refine_env_vars`, `wizard_generate_code`
**Sync** (wait for result): `wizard_create_session`, `wizard_chat`, `wizard_list_tools`, `wizard_submit_tools`, `wizard_list_env_vars`, `wizard_submit_env_vars`, `wizard_set_auth`, `wizard_regenerate_tool_code`, `wizard_deploy`, `wizard_state`
---
## The Wizard Pipeline
```
1. wizard_create_session → Returns server_id (save it, needed everywhere)
2. wizard_chat (loop) → Gather requirements; stop when is_ready: true
3. wizard_start → Transition to tool suggestion (async → poll)
4. wizard_list_tools → Review AI-suggested tools
5. wizard_refine_tools → Iterate on tools until satisfied (optional, async → poll)
6. wizard_submit_tools → Confirm selection by tool UUID list
7. wizard_list_env_vars → Review suggested env vars
8. wizard_refine_env_vars → Iterate on env vars (optional, async → poll)
9. wizard_submit_env_vars → Provide values as {uuid: value} dict (call even if empty)
10. wizard_set_auth → Generate bearer token
11. wizard_generate_code → Trigger code generation (async → poll)
12. wizard_deploy → Deploy → returns server_url + bearer_token
```
**Always call `wizard_submit_env_vars`**, even when `wizard_list_env_vars` returns `[]`. Pass an empty dict `{}` so the backend transitions to the next state.
---
## 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`.
---
## Polling Pattern
After any async tool, poll `wizard_state` until `processing_status` is `"idle"`:
```
wizard_state(server_id) → check .processing_status
"processing" → wait and call again
"idle" → ready for next step
"error" → check .processing_error
```
---
## Connecting a Deployed Server to MCP Clients
After `wizard_deploy`, construct the full server URL:
```
https://api.mcphero.app{server_url}
```
where `server_url` is the relative path returned (e.g., `/mcp/<server-id>/mcp`).
### Claude Desktop config
```json
{
"mcpServers": {
"my-server": {
"url": "https://api.mcphero.app/mcp/<server-id>/mcp",
"headers": {
"Authorization": "Bearer <bearer_token>"
}
}
}
}
```
---
## 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 `wizard_create_session`. Every subsequent call needs it.
**Empty env vars**: Even if `wizard_list_env_vars` returns `[]`, you must still call `wizard_submit_env_vars` with `{}` 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).