# The Aggregate — LLM benchmark aggregate

- Registry name: `ai.theaggregate/the-aggregate` · version 1.0.2
- 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=ai.theaggregate%2Fthe-aggregate
- Server page: https://mcpstation.net/s/ai.theaggregate--the-aggregate.html

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

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

## Connect

- streamable-http: `https://theaggregate.ai/mcp`

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

- `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 paging via limit/offs
- `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.

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