Fused LLM rankings: one IRT/Elo scale across ~5,000 public benchmark leaderboards, updated daily.
Inferido de los transportes que declara este listado (streamable-http). Que un cliente no aparezca aquí no significa que se haya descartado: simplemente Forge no puede confirmarlo.
La verificación confirma la identidad del publicador (la propiedad del repo), no la seguridad del código. El análisis de seguridad cubre los CVE conocidos y los scripts de instalación sospechosos.
Leído de un handshake MCP real initialize → tools/list contra el endpoint declarado. No se invocó ninguna herramienta: tools/list es la llamada de introspección de solo lectura que el protocolo define para esto. Refleja lo que el servidor anunciaba en ese momento; un endpoint alojado no está fijado a ninguna versión y puede cambiar sin avisar.
https://theaggregate.ai/mcp8 herramientas · 147 msget_leaderboardTop of the cross-benchmark aggregate ranking: every model placed on one Elo 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/offset.Top of the cross-benchmark aggregate ranking: every model placed on one Elo 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/offset.
| Parámetro | Tipo | Descripción |
|---|---|---|
| limit | number | Rows to return (1-100, default 25). |
| offset | number | Rows to skip from the top (default 0). |
| include_variants | boolean | Rank each reasoning-effort variant separately (e.g. "Claude Opus 4.6 (High)") instead of one fused row per model. Default false. |
search_modelsFind ranked models by (partial) name or provider. Returns rank, Elo and the model page URL. One row per model by default, fused across reasoning-effort settings.Find ranked models by (partial) name or provider. Returns rank, Elo and the model page URL. One row per model by default, fused across reasoning-effort settings.
| Parámetro | Tipo | Descripción |
|---|---|---|
| query* | string | Model or provider name fragment, e.g. "opus" or "deepseek". |
| limit | number | Max results (1-25, default 10). |
| include_variants | boolean | Return each reasoning-effort variant separately (e.g. "Claude Opus 4.6 (High)") instead of one fused row per model. Default false. |
get_modelOne model in depth: aggregate rank, Elo with standard error, provider, what it is, cost per task where known, and its most notable benchmark results (with percentiles).One model in depth: aggregate rank, Elo with standard error, provider, what it is, cost per task where known, and its most notable benchmark results (with percentiles).
| Parámetro | Tipo | Descripción |
|---|---|---|
| model* | string | Model name or slug, e.g. "Claude Opus 4.5" or "gpt-5-5". |
compare_modelsHead-to-head between 2-4 models: aggregate ranks, Elo gap with a significance note based on the standard errors, and notable benchmarks they share.Head-to-head between 2-4 models: aggregate ranks, Elo gap with a significance note based on the standard errors, and notable benchmarks they share.
| Parámetro | Tipo | Descripción |
|---|---|---|
| models* | array | Two to four model names or slugs. |
search_benchmarksFind benchmarks in the aggregate by (partial) name. Returns model coverage, difficulty on the Elo scale, and the benchmark page URL.Find benchmarks in the aggregate by (partial) name. Returns model coverage, difficulty on the Elo scale, and the benchmark page URL.
| Parámetro | Tipo | Descripción |
|---|---|---|
| query* | string | Benchmark name fragment, e.g. "swe-bench" or "arena". |
| limit | number | Max results (1-25, default 10). |
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.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.
| Parámetro | Tipo | Descripción |
|---|---|---|
| benchmark* | string | Benchmark name or slug, e.g. "Aider polyglot". |
| top | number | How many top models to list (1-50, default 10). |
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.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.
No se publicó ningún esquema de entrada para esta herramienta.
about_the_aggregateWhat this data is: how the IRT fusion works, current coverage counts, update cadence, and how to cite it.What this data is: how the IRT fusion works, current coverage counts, update cadence, and how to cite it.
No se publicó ningún esquema de entrada para esta herramienta.
8 de 8 herramientas publicaron una descripción.
Los nombres y descripciones de las herramientas los escribe el publicador y se muestran literalmente como texto inerte. Son las cadenas que un cliente MCP pasa al modelo, así que Forge las analiza en busca de patrones de inyección de prompts — cualquier hallazgo aparece junto al análisis de seguridad de arriba. «Privilegiada» es una coincidencia de palabra clave en el nombre de la herramienta, no una auditoría de lo que hace: un nombre inofensivo puede hacer cualquier cosa.
Fused LLM rankings: one IRT/Elo scale across ~5,000 public benchmark leaderboards, updated daily.
Los nombres enlazados abren el índice de Forge con todas las entradas que se observó que exponen esa herramienta. Ver todas las herramientas indexadas.
Esta entrada no publica ningún paquete de npm, así que Forge no tiene un árbol de dependencias para ella. Es una carencia de cobertura, no una afirmación de que no tenga dependencias.