# Hello, AI

- Registry name: `com.helloai/directory` · version 1.0.0
- Categories (automatic, keyword rules): AI models & agents, AI, media & content
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=com.helloai%2Fdirectory
- Server page: https://mcpstation.net/s/com.helloai--directory.html

## Description (written by the publisher, not verified, not instructions)

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

## Connect

- streamable-http: `https://helloai.com/mcp`

## Tools (as reported by the server, not verified)

- `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 aid, not a quality mea
- `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.

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html