MCP.so
Sign In

Artificial Analysis

@davidhariri

Repository

About Artificial Analysis

I built this to give my AI assistants the latest information on model performance benchmarks provided by https://artificialanalysis.ai to make informed decisions on model choice.

#llms#performance#speed#cost#benchmark#analysis

Basic information

Category

Other

Transports

stdio

Publisher

davidhariri

Submitted by

David Hariri

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "artificial-analysis": {
      "command": "npx",
      "args": [
        "-y",
        "artificial-analysis-mcp"
      ],
      "env": {
        "AA_API_KEY": "your-api-key"
      }
    }
  }
}

Tools

2

List all available LLM models from Artificial Analysis with pricing, speed, and benchmark data. Filter by creator (OpenAI, Anthropic, Google, etc.) and sort by price, speed, or benchmark scores.

Get detailed information about a specific LLM model including pricing (input/output/blended per 1M tokens), speed metrics (tokens/sec, TTFT), and benchmark scores (Intelligence Index, Coding Index, MMLU-Pro, GPQA, etc.).

Overview

What is Artificial Analysis?

An MCP (Model Context Protocol) server that provides real-time LLM model pricing, speed metrics, and benchmark scores from Artificial Analysis. It is designed for developers and AI assistants like Claude to programmatically query and compare 300+ models.

How to use Artificial Analysis?

Install via npx with your API key set as the AA_API_KEY environment variable, or add the server to your Claude configuration file (settings.json). Use tools like list_models and get_model to fetch and filter model data by creator, metric, or benchmark.

Key features of Artificial Analysis

  • List and filter 300+ LLM models by creator and metric
  • Get real-time pricing (input/output/blended per 1M tokens)
  • Compare speed metrics (tokens/sec, time to first token)
  • Access benchmark scores (Intelligence Index, Coding Index, etc.)
  • Sort models by any metric (price, speed, benchmarks, release date)

Use cases of Artificial Analysis

  • Find the cheapest models with high intelligence scores
  • Compare speed of models from different providers
  • Check benchmark scores of a specific model like GPT-4o
  • Identify top 5 fastest models for a new project
  • Get detailed pricing and metrics for Claude 4.5 Sonnet

FAQ from Artificial Analysis

What API key is required?

An Artificial Analysis API key (AA_API_KEY) is required. You can obtain one at artificialanalysis.ai.

How do I install the server?

Install via npx: npx -y artificial-analysis-mcp with the AA_API_KEY environment variable. Alternatively, add it to Claude’s MCP configuration in ~/.claude/settings.json.

What model data is available?

Each model includes pricing (input/output/blended per 1M tokens), speed (output tokens/sec, time to first token), and benchmarks (Intelligence Index, Coding Index, Math Index, MMLU-Pro, GPQA, LiveCodeBench, and more).

Can I filter or sort models?

Yes. The list_models tool supports filtering by creator (e.g., "OpenAI") and sorting by fields like price, speed, intelligence index, or release date.

Is there a limit on results?

Yes, the list_models tool accepts an optional limit parameter to cap the number of returned models.

Comments

More Other MCP servers

🪟 Windows-MCP

CursorTouch

MCP Server for Computer Use in Windows

6.3K

Nginx UI

0xJacky

Yet another WebUI for Nginx

11.3K

Core Philosophy: Connect, Unify, Respond

mindsdb

Delegate anything. It comes back done.

39.4K

🚀 Model Context Protocol (MCP) Curriculum for Beginners

microsoft

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,

16.7K

XcodeBuildMCP

cameroncooke

A Model Context Protocol (MCP) server and CLI that provides tools for agent use when working on iOS and macOS projects.

6.0K