AI & Machine Learning
hordus.ai
Monitor brand visibility and share of voice across major AI platforms like ChatGPT and Claude.
ENDPOINT 1
https://www.hordus.ai/mcp
MCP server metadata
- Name
- Hordus AI MCP Server
- Version
- 1.0.0
Known tools 2
getBrandVisibilityRetrieve AI visibility score and Answer Share of Voice (A-SOV) for a specific brand across ChatGPT, Claude, Gemini, and Perplexity.
Inferred read-onlyget_latest_blog_postsRetrieve the latest blog posts from Hordus AI, including titles, slugs, authors, and publication dates.
Inferred read-onlyCONNECT 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.hordus-ai-mcp-server]
url = "https://www.hordus.ai/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"hordus-ai-mcp-server": {
"type": "http",
"url": "https://www.hordus.ai/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: hordus-ai-mcp-server
Remote MCP URL: https://www.hordus.ai/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": {
"hordus-ai-mcp-server": {
"url": "https://www.hordus.ai/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"hordus-ai-mcp-server": {
"type": "http",
"url": "https://www.hordus.ai/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "hordus-ai-mcp-server",
"transport": "streamable-http",
"url": "https://www.hordus.ai/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Trust Data Available
BuiltWith Trust API v2 evidence for hordus.ai was fetched 2026-08-03T22:23:39.209Z and is being refreshed.
hordus.ai is assessed as Trusted: Domain runs a meaningful technology spend, consistent with a real business.
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.