What API key is required?
An Artificial Analysis API key (`AA_API_KEY`) is required. You can obtain one at [artificialanalysis.ai](https://artificialanalysis.ai).
@davidhariri
基本信息
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.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"artificial-analysis": {
"command": "npx",
"args": [
"-y",
"artificial-analysis-mcp"
],
"env": {
"AA_API_KEY": "your-api-key"
}
}
}
}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.).
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.
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.
An Artificial Analysis API key (`AA_API_KEY`) is required. You can obtain one at [artificialanalysis.ai](https://artificialanalysis.ai).
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`.
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).
Yes. The `list_models` tool supports filtering by creator (e.g., "OpenAI") and sorting by fields like price, speed, intelligence index, or release date.
Yes, the `list_models` tool accepts an optional `limit` parameter to cap the number of returned models.

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