INDIVIDUAL MCP TOOL
growthr_fix_order
Run the scan and sort every failed check into buckets: blockers (fix before anything else, they hide everything downstream), this afternoon (metadata, llms.
LIVE ENDPOINT
https://mcp.growthr.com/mcp
Connect to this endpoint to inspect the live schema for growthr_fix_order and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Inferred read-only · medium confidence · heuristic, not a guarantee.
- No write-capable action terms were found; this is not proof that invocation has no side effects.
Parent server
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.growthr]
url = "https://mcp.growthr.com/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"growthr": {
"type": "http",
"url": "https://mcp.growthr.com/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: growthr
Remote MCP URL: https://mcp.growthr.com/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"growthr": {
"url": "https://mcp.growthr.com/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"growthr": {
"type": "http",
"url": "https://mcp.growthr.com/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "growthr",
"transport": "streamable-http",
"url": "https://mcp.growthr.com/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
growthr_scan— Fetch a public domain the way search engines and AI crawlers do (ChatGPT's GPTBot, Claude's ClaudeBot, and the fetchers behind Perplexity and Google AI Overviews: from a datacenter IP, no JavaScript) and run 22 weighted checks: reachability as a browser, GPTBot, and ClaudeBot; server-rendered content; metadata; strict JSON-LD and Organization schema; robots.growthr_llms_txt— Read a site's homepage, sitemap (or homepage links), and up to twelve pages, then draft an llms.growthr_ai_visibility— Run one buyer-shaped prompt through Gemini with Google Search grounding (a real, cited web search, the same mechanism behind Google AI Overviews) and report where the brand lands on the five-rung ladder: absent, cited (a page of the brand's site is a source), mentioned (named in the text), recommended (on the shortlist), or recommended against.