create-mcp-server

name	create-mcp-server
description	Create, deploy, and manage MCP (Model Context Protocol) servers using the MCPHero platform via the mcpheroctl CLI. Use this skill when the user wants to build an MCP server, deploy tools that wrap APIs or databases, automate MCP server creation, or connect AI clients (Claude Desktop, Cursor, etc.) to custom tools through MCPHero.

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.

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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.

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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  --json




mcpheroctl wizard submit-env-vars  --json \
  --var  \
  --var 

mcpheroctl wizard submit-env-vars  --json


mcpheroctl wizard set-auth  --json



mcpheroctl wizard generate-code  --json
 mcpheroctl wizard state  --json 2>/dev/null | \
  python3 -c ; 
   3



mcpheroctl wizard deploy  --json

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

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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.

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Exit Codes

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