About Artificial Analysis
Artificial Analysis is an MCP server that provides AI assistants with LLM pricing, speed, and benchmark data from Artificial Analysis. It supports filtering and sorting model listings, as well as retrieving details for a specific model.
Key features
- 01Look up LLM input and output prices
- 02Compare generation speed and time to first token
- 03View multiple benchmark scores
- 04Filter models by provider
- 05Sort models by metric
Use cases
- 01Compare prices across models
- 02Find models with higher speed
- 03Assess models using benchmark scores
- 04Retrieve metrics for a specific model
MCP support
The MCP server exposes tools to list and inspect models, including filtering by provider and sorting by metric. It provides pricing, speed, and benchmark data and requires an Artificial Analysis API key.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
2Saved tool list · updated 3w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| creator | string | No | Filter by model creator (e.g., "OpenAI", "Anthropic", "Google") |
| sort_by | enum | No | Field to sort byprice_input | price_output | price_blended | speed | ttft | intelligence_index | coding_index | math_index | mmlu_pro | gpqa | release_date |
| sort_order | enum | No | Sort order (default: desc)asc | desc |
| limit | number | No | Maximum number of results to return |
Details
From the project READMEArtificial Analysis MCP Server
An MCP (Model Context Protocol) server that provides LLM model pricing, speed metrics, and benchmark scores from Artificial Analysis.
Features
- Get real-time pricing for 300+ LLM models (input/output/blended rates)
- Compare speed metrics (tokens/sec, time to first token)
- Access benchmark scores (Intelligence Index, Coding Index, MMLU-Pro, GPQA, and more)
- Filter by provider (OpenAI, Anthropic, Google, etc.)
- Sort by any metric
Installation
Claude Code
claude mcp add artificial-analysis -e AA_API_KEY=your-key -- npx -y artificial-analysis-mcp
Or install from GitHub:
claude /mcp add https://github.com/davidhariri/artificial-analysis-mcp
Manual Configuration
Add to your Claude settings (~/.claude/settings.json):
{
"mcpServers": {
"artificial-analysis": {
"command": "npx",
"args": ["-y", "artificial-analysis-mcp"],
"env": {
"AA_API_KEY": "your-api-key"
}
}
}
}
Configuration
| Environment Variable | Required | Description |
|---|---|---|
AA_API_KEY | Yes | Your Artificial Analysis API key |
Get your API key at artificialanalysis.ai.
Tools
list_models
List all available LLM models with optional filtering and sorting.
Parameters:
| Name | Type | Required | Description |
|---|---|---|---|
creator | string | No | Filter by model creator (e.g., "OpenAI", "Anthropic") |
sort_by | string | No | Sort field (see below) |
sort_order | string | No | "asc" or "desc" (default: "desc") |
limit | number | No | Maximum results to return |
Sort fields: price_input, price_output, price_blended, speed, ttft, intelligence_index, coding_index, math_index, mmlu_pro, gpqa, release_date
Example usage:
- "List the top 5 fastest models"
- "Show me Anthropic models sorted by price"
- "What are the cheapest models with high intelligence scores?"
get_model
Get detailed information about a specific model.
Parameters:
| Name | Type | Required | Description |
|---|---|---|---|
model | string | Yes | Model name or slug (e.g., "gpt-4o", "claude-4-5-sonnet") |
Returns: Complete model details including pricing, speed metrics, and all benchmark scores.
Example usage:
- "Get pricing for GPT-4o"
- "What are Claude 4.5 Sonnet's benchmark scores?"
Model Data
Each model includes:
- Pricing: Input/output/blended rates per 1M tokens (USD)
- Speed: Output tokens per second, time to first token
- Benchmarks: Intelligence Index, Coding Index, Math Index, MMLU-Pro, GPQA, LiveCodeBench, and more
Development
# Install dependencies
npm install
# Build
npm run build
# Run locally
AA_API_KEY=your-key node dist/index.js
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.