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Hello, AI MCP server

Which MCP servers are Hello, AI's own, from the official registry and from asking its own domain, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.

read 2026-10-27

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Whose server it is
  • Registry namecom.helloai/directoryverified in the MCP registry

The registry name sits under helloai.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.

When we asked itchecked 2026-10-27
  • Stateanswerschecked 2026-10-27
  • Tools6
  • Server calls itselfhelloai
  • Server version2.14.85
  • Protocol version2025-06-18

On 2026-10-27 the server answered initialize and tools/list without a sign-in. First answer in 75 ms.

Should an agent connect itConnect it
  • Its tools do every use case we checked: compare AI model rankings by task and price; check current leaderboard scores and context limits.

Once connected

  • For "compare AI model rankings by task and price", the likely first call is recommend_models.
  • For "check current leaderboard scores and context limits", the likely first call is list_models.

Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.

Measured dailydaily checks: 7, the first on 2026-10-27
  • INITE MCP score100 of 100answers 100 · does the job 100 · definitions 100 · context 100 · connects 100
  • What an agent can do with it2 of 2 use cases
  • Answered100% of days7 of 7 daily checks
  • Median first answer286 ms
  • Space in an agent's context≈ 681 tokensthe definitions of all its tools (6), which an agent carries on every turn
  • Tool definitionsA · 100 of 100
  • Typed results0 of 6 toolsdeclared outputSchema: results come typed, read once
  • Every tool passes all six checks.

What an agent can do with it

  • can do · compare AI model rankings by task and price
  • not sure · find open-weight models that run on a local GPU
  • can do · check current leaderboard scores and context limits

Each of the product's use cases, put to Jev against this server's tool list: can an agent do it with these tools?

Worth a look

None of the five warning signs in these definitions.

A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →

Tools it offers6 tools · read 2026-10-27
  • 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…

  • 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.

How to connect

Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:

{
  "mcpServers": {
    "directory": {
      "type": "http",
      "url": "https://helloai.com/mcp"
    }
  }
}

Add it

Claude Code, in a terminal

claude mcp add --transport http helloai https://helloai.com/mcp

Add to CursorAdd to VS Code

claude.ai, ChatGPT and other clients: add https://helloai.com/mcp as a custom connector in the settings.

Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.