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The Aggregate — LLM benchmark aggregate

by theaggregate.ai in AI models & inference

MCP serverPassing, checked 8 h ago

LLM rankings from public benchmarks, model comparisons and source-linked results. Updated daily.

https://theaggregate.ai/mcp
Tools
8
open to any client
Uptime
100%
last 30 days
Response time
303 ms
533 ms slowest 5%
Last check
Passed
8 h ago, next any minute now

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How to connect

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "the-aggregate-llm-benchmark-aggregate": {
      "type": "http",
      "url": "https://theaggregate.ai/mcp"
    }
  }
}

8 tools

  • get_leaderboard

    Top of the cross-benchmark aggregate ranking: every model placed on one rating scale by an IRT model fit over public benchmark leaderboards (call about_the_aggregate for the current coverage counts). One row per model by default, fused across reasoning-effort settings. Supports…

  • search_models

    Find ranked models by (partial) name or provider. Returns rank, Aggregate Rating and the model page URL. One row per model by default, fused across reasoning-effort settings.

  • get_model

    One model in depth: aggregate rank, Aggregate Rating with standard error, provider, what it is, cost per task where known, and its most notable benchmark results (with percentiles).

  • compare_models

    Head-to-head between 2-4 models: aggregate ranks, rating gap with a significance note based on the standard errors, and notable benchmarks they share.

  • search_benchmarks

    Find benchmarks in the aggregate by (partial) name. Returns model coverage, difficulty on the rating scale, and the benchmark page URL.

  • get_benchmark

    One benchmark in depth: what it measures, the original source leaderboard URL, IRT stats (difficulty, noise, model coverage), skill weights, and the current top models on it.

  • get_prediction_duel

    Guesswork — the public prediction duel: every day frontier LLMs and The Aggregate's own IRT model predict newly scraped benchmark scores before seeing them, and the errors are scored. Returns the current monthly standings, wins and losses included.

  • about_the_aggregate

    What this data is: how the IRT fusion works, current coverage counts, update cadence, and how to cite it.

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