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The Aggregate — LLM benchmark aggregate
ai.theaggregate/the-aggregate · v1.0.2
Measured by MCP Station
| Last check | Reachable |
|---|---|
| Checked at | — |
| Check success 7 / 30 days | — |
| First-try success 30 days | — |
| Median response | — |
| Lookups 30 days | — |
| Authentication | No auth |
| MCP version | 2025-06-18 |
| Rank score | — |
| Declared risk | Read-only (all tools declare readOnlyHint) |
| Capabilities declared | tools |
| Tool definitions | 8 tools · with description 100% · input schema is an object 100% · read/destructive hints 100% |
Description written by the publisher, not verified
LLM rankings from public benchmarks, model comparisons and source-linked results. Updated daily.
Connect
streamable-http · https://theaggregate.ai/mcp
claude mcp add --transport http the-aggregate https://theaggregate.ai/mcp{
"mcpServers": {
"the-aggregate": {
"url": "https://theaggregate.ai/mcp"
}
}
}Tools as reported by the server
get_leaderboardTop 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 paging via limit/offssearch_modelsFind 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_modelOne 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_modelsHead-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_benchmarksFind benchmarks in the aggregate by (partial) name. Returns model coverage, difficulty on the rating scale, and the benchmark page URL.get_benchmarkOne 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_duelGuesswork — 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_aggregateWhat this data is: how the IRT fusion works, current coverage counts, update cadence, and how to cite it.
Website · JSON · Text for agents · Registry updated 2026-10-09