Askedthrice MCP server
{
"mcpServers": {
"askedthrice": {
"type": "http",
"url": "https://mcp.askedthrice.com/mcp"
}
}
}{
"mcpServers": {
"askedthrice": {
"type": "http",
"url": "https://mcp.askedthrice.com/mcp"
}
}
}{
"mcpServers": {
"askedthrice": {
"type": "http",
"url": "https://mcp.askedthrice.com/mcp"
}
}
}{
"servers": {
"askedthrice": {
"type": "http",
"url": "https://mcp.askedthrice.com/mcp"
}
}
}{
"mcpServers": {
"askedthrice": {
"type": "http",
"url": "https://mcp.askedthrice.com/mcp"
}
}
}file .mcp.json (in your project root)file claude_desktop_config.jsonfile ~/.cursor/mcp.jsonfile .vscode/mcp.jsonfile ~/.codeium/windsurf/mcp_config.jsoninstall npx -y askedthrice-mcpversion 0.1.0
What it does
MCP server for askedthrice.com that measures whether a brand appears in AI assistant recommendations when buyers ask for suggestions. It runs live audits across multiple AI providers and returns measured results showing which brands won each recommendation question.
- Track whether your brand gets recommended when potential buyers ask AI assistants for product suggestions in your category.
- Compare your brand's actual visibility in AI recommendations against competitors by measuring real recommendation queries.
- Monitor changes in AI recommendation patterns for your brand over time with periodic visibility checks.
Tools this server exposes
| Tool | Does |
|---|---|
| start_visibility_check | Initiates a visibility measurement for a brand and returns a runId to track the audit. |
| get_visibility_check | Retrieves the results of a visibility check using a runId, returning the measured map of which brands won each buyer question. |
Before you enable it
An MCP server runs with whatever access you give it. Start with a development account rather than production, and check which tools the server exposes before you let an agent call them unattended.