Visibility Index MCP server
{
"mcpServers": {
"dabyte-visibility-index": {
"type": "http",
"url": "https://dabyte.ai/mcp"
}
}
}{
"mcpServers": {
"dabyte-visibility-index": {
"type": "http",
"url": "https://dabyte.ai/mcp"
}
}
}{
"mcpServers": {
"dabyte-visibility-index": {
"type": "http",
"url": "https://dabyte.ai/mcp"
}
}
}{
"servers": {
"dabyte-visibility-index": {
"type": "http",
"url": "https://dabyte.ai/mcp"
}
}
}{
"mcpServers": {
"dabyte-visibility-index": {
"type": "http",
"url": "https://dabyte.ai/mcp"
}
}
}file .mcp.json (in your project root)file claude_desktop_config.jsonfile ~/.cursor/mcp.jsonfile .vscode/mcp.jsonfile ~/.codeium/windsurf/mcp_config.jsonversion 1.0.1
What it does
This MCP server exposes weekly measurements of how often AI assistants (ChatGPT, Perplexity, Gemini) name specific brands in response to category buyer prompts. It covers two niches: SaaS/AI tools (20 brands via dabyte.ai) and Crypto/Web3 (24 brands via dablock.ai). It is aimed at developers and analysts who want to query AI visibility data programmatically.
- Retrieve the current share-of-answer score for a SaaS brand across ChatGPT, Perplexity, and Gemini.
- Query the full historical time series of AI visibility measurements for a specific brand.
- Fetch derived rankings such as most visible brands or brands with high commercial intent but low AI visibility.
Tools this server exposes
| Tool | Does |
|---|---|
| aiv_current | Returns the latest share-of-answer measurement for tracked brands, including per-engine scores, rank, and quadrant. |
| aiv_history | Returns the full time series of past measurements for tracked brands across all published releases. |
| aiv_rankings | Returns derived ranking lists such as most visible brands, invisible-despite-demand, and top movers. |
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.