INDIVIDUAL MCP TOOL

get_leaderboard

Top of the cross-benchmark aggregate ranking: every model placed on one Elo scale by an IRT model fit over ~5,000 public benchmark leaderboards.

theaggregate.ainone authenticationAvailability not checked

LIVE ENDPOINT

https://theaggregate.ai/mcp

No auth detected

Connect to this endpoint to inspect the live schema for get_leaderboard and invoke it with your own arguments.

{}

Inferred read-only · medium confidence · heuristic, not a guarantee.

No write-capable action terms were found; this is not proof that invocation has no side effects.

CONNECT WITH APPROVAL

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.the-aggregate]
url = "https://theaggregate.ai/mcp"
enabled = true

Claude Code

.mcp.json

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

Claude Desktop

Settings → Connectors → Add custom connector

Name: the-aggregate
Remote MCP URL: https://theaggregate.ai/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "the-aggregate": {
      "url": "https://theaggregate.ai/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

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

Generic MCP

Client-specific MCP configuration

{
  "name": "the-aggregate",
  "transport": "streamable-http",
  "url": "https://theaggregate.ai/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

search_models — Find ranked models by (partial) name or provider.
get_model — 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).
compare_models — 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.
search_benchmarks — Find benchmarks in the aggregate by (partial) name.
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.
about_the_aggregate — What this data is: how the IRT fusion works, current coverage counts, update cadence, and how to cite it.