agentsclimarketplace

Meta mcp wizard

Skill arterialist/mcphero-skills/skills/meta-mcp-wizard

Agent Skills for mcphero.app - let your OpenClaw or coding agents create deployed MCP servers on the fly in just 30 seconds.

Install
npx -y skills add arterialist/mcphero-skills --skill meta-mcp-wizard

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

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.

SKILL.md

6.3 KB, ~1.4k tokens by cl100k_base, as published. Nobody here has run it

Meta-MCP Wizard

The MCPHero 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

// ~/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%\Claude\claude_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:

ToolPurpose
wizard_create_sessionStart session; returns server_id
wizard_chatSend requirement message; returns is_ready flag
wizard_startTransition to tool suggestion (async)
wizard_list_toolsList suggested tools with IDs, code, params
wizard_refine_toolsRefine with feedback (async)
wizard_submit_toolsConfirm selection by tool UUID list
wizard_suggest_env_varsRe-trigger env var suggestion (async)
wizard_list_env_varsList env vars with IDs and descriptions
wizard_refine_env_varsRefine env vars with feedback (async)
wizard_submit_env_varsSubmit values as {uuid: value} dict
wizard_set_authGenerate bearer token
wizard_generate_codeTrigger code gen (async)
wizard_regenerate_tool_codeRegenerate single tool code (sync)
wizard_deployDeploy and get server URL
wizard_statePoll 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

{
  "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).

What ships with it: 1 file

3.0 KB alongside SKILL.md

evals/

Gives 0 of the 12 instructions most mcp tooling skills give in ~1.4k tokens

Counted across 638 of the 750 authors here whose files we hold, read 2026-08-07

  • Create ten complex or independent read-only evaluation questionsin 69 of 638, across 15 files
  • Test servers using MCP Inspectorin 61 of 638, across 19 files
  • Provide actionable error messages with specific next stepsin 54 of 638, across 12 files
  • Prioritize comprehensive API coverage over specific workflows or workflow toolsin 54 of 638, across 12 files
  • Use TypeScript and Streamable HTTP for remote servers or clientsin 54 of 638, across 8 files
  • Define structured output schemas where possiblein 50 of 638, across 8 files
  • Use Zod or Pydantic for input schemasin 47 of 638, across 5 files
  • Fetch MCP specification pages with markdown suffixin 46 of 638, across 4 files
  • Load framework documentation using WebFetchin 45 of 638, across 3 files
  • Verify each evaluation answer independentlyin 45 of 638, across 3 files
  • Implement API client with authentication and paginationin 45 of 638, across 3 files
  • Define input schemas with validationin 27 of 638, across 9 files

Said here and by no other author read

  • add the meta-mcp endpoint to client config
  • save the returned server_id
  • include the server_id in every subsequent call
  • loop the chat tool until is_ready is true
  • call wizard_submit_env_vars even when list is empty
  • submit at most five tools per server

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.