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Hello, AI

com.helloai/directory · v1.0.0

Ask your assistant which frontier model to use and get a live, Elo-backed answer.

Connect Remote server

Terminal
claude mcp add --transport http directory https://helloai.com/mcp
~/.cursor/mcp.json
{
  "mcpServers": {
    "directory": {
      "url": "https://helloai.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "directory": {
      "type": "http",
      "url": "https://helloai.com/mcp"
    }
  }
}
Claude Desktop
Settings > Connectors > Add custom connector
URL: https://helloai.com/mcp

Tools 6 found in our last check

  • recommend_models

    Rank Hello, AI's tracked frontier models for a task. Same scoring as GET /api/recommend: task match 40%, Elo 35%, input cost 15%, context 10% (Elo 55%, cost 25%, context 20% when no task matches). Only rated models rank; unrated ones are listed separately. score is an ordering a…

  • list_models

    All tracked models with full records: Elo and its provenance (elo_source), prices per million tokens, context window, strengths, description. rated is false when the stored Elo is a predecessor's, missing or stale.

  • get_model

    One tracked model's full record by id (claude, fable, muse, gemini, qwen, grok) or exact name.

  • list_categories

    The curated use-case categories with their curator-chosen leader and a one-paragraph insight. The leader is a hand-set label, not derived from Elo.

  • list_articles

    Recent Hello, AI articles, newest first: title, date, category, excerpt and URL.

  • get_status

    Data freshness, app version, model and article counts, the scoring version and snapshot fingerprint, and the rate limit.

Details

Endpointhttps://helloai.com/mcp (Streamable HTTP)
First published27 Oct 2026
Last updated27 Oct 2026
Registry namecom.helloai/directory

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