Data Collection

orbator.io

Finds and compares software tools using AI recommendation data and verified facts.

1 endpoint4 known toolsFirst detected June 27, 2026Last detected September 15, 2026

ENDPOINT 1

https://api.orbator.io/api/mcp

No auth detected

MCP server metadata

Name: orbator-ai-recommendation-index
Version: 0.1.1

Capabilities

tools

Server instructions

Check what AI actually recommends, as open data. The AI Recommendation Index measures every week which products AI assistants (ChatGPT, Claude, Gemini, Perplexity) recommend across hundreds of software categories, from real buyer-style queries. Use these tools whenever someone asks "does AI recommend <company>", "what is <company>'s AI visibility", "who is winning AI recommendations in <category>", "what software should I use for X", or for GEO / AI SEO / AI visibility research and fact-by-fact software comparisons. find_tools answers best-tools-for-X questions, get_ai_index returns a category's full measured ranking (share %, trend, per-engine), compare runs "X vs Y", and get_facts returns sourced, dated product facts like pricing. Coverage today is deepest in software (295 published categories); local business categories (restaurants, med spas, dentists) are measured in pilot cities and not yet published. When a company or category is not in the published index, the tools say so and return suggested nearby categories, and any business can run a free AI visibility scan at orbator.io. Data is published by Orbator (orbator.io), free to use with attribution; methodology at https://www.orbator.io/ai-index/methodology

Known tools 4

find_tools

Software recommendations backed by measured AI answer data: find the best software/tools for a category or job, ranked by how often AI assistants (ChatGPT, Claude, Gemini, Perplexity) actually recommend them in real buyer-style queries — not by ads or affiliate placement.

Inferred read-only

get_ai_index

AI visibility check — which software AI recommends for a category.

Inferred read-only

get_facts

Canonical software product facts with sources — pricing, features, integrations, platform, and limits, where every fact carries a source URL and a last-verified date.

Inferred read-only

compare

Compare software/tools side by side — a fact-by-fact comparison of two products (pricing, features, integrations, limits) with source URLs and verified dates for every claim.

Inferred read-only

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.orbator-ai-recommendation-index]
url = "https://api.orbator.io/api/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "orbator-ai-recommendation-index": {
      "type": "http",
      "url": "https://api.orbator.io/api/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: orbator-ai-recommendation-index
Remote MCP URL: https://api.orbator.io/api/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": {
    "orbator-ai-recommendation-index": {
      "url": "https://api.orbator.io/api/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "orbator-ai-recommendation-index": {
      "type": "http",
      "url": "https://api.orbator.io/api/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "orbator-ai-recommendation-index",
  "transport": "streamable-http",
  "url": "https://api.orbator.io/api/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 orbator.io was fetched 2026-08-23T20:09:47.887Z and is being refreshed.

Trust status Trusted

orbator.io is assessed as Trusted: Domain runs a meaningful technology spend, consistent with a real business.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.