@A7OM-AI
ATOM: The Global Price Benchmark for AI Inference. MCP server access to the AIPI index family.
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"atom-pricing-intelligence": {
"url": "https://atom-mcp-server-production.up.railway.app/mcp"
}
}
}Search and filter AI inference models across all tracked vendors and SKUs. Query by modality (Text, Image, Audio, Video, Multimodal), vendor, creator, model family, open-source status, price range, context window, and parameter count. Returns matching models with pricing. Free tier shows count + price range; paid tier shows full details. Examples: - "Find open-source text models under $1/M tokens" → open_source=true, modality="Text", max_price=0.001 - "What multimodal models does Google offer?" → vendor="Google", modality="Multimodal" - "Models with 128K+ context window" → min_context_window=128000
Deep dive on a single AI model: technical specs + pricing across all vendors. Returns model_registry data (context window, parameters, open-source status, training cutoff, model family) plus all SKU pricing across every vendor that offers this model. Examples: - "Tell me everything about GPT-4o" → model_name="GPT-4o" - "Claude Sonnet 4.5 specs and pricing" → model_name="Claude Sonnet 4.5"
Cross-vendor price comparison for a specific model or model family. Shows the same model (or family) priced across different vendors, sorted cheapest first. Essential for cost optimization and vendor selection. Examples: - "Compare Llama 3.1 70B pricing across vendors" → model_name="Llama 3.1 70B" - "Cheapest GPT-4 family output pricing" → model_family="GPT-4", direction="Output" - "Claude pricing comparison" → model_family="Claude"
Full catalog for a specific vendor: all models, modalities, and pricing. Returns vendor metadata (country, region, pricing page URL) plus every model and SKU they offer. Examples: - "What does Together AI sell?" → vendor="Together AI" - "OpenAI's text model pricing" → vendor="OpenAI", modality="Text" - "Amazon Bedrock catalog" → vendor="Amazon Bedrock"
Aggregate AI inference market intelligence. Returns total vendor/model/SKU counts, price distribution (median, mean, quartiles, min/max), and modality breakdown. Optionally filter by modality. Examples: - "AI inference market overview" → (no params) - "Text model pricing statistics" → modality="Text" - "Image generation market stats" → modality="Image"
AIPI (ATOM Inference Price Index) — chained matched-model price benchmarks for AI inference. Returns benchmark indexes across four categories: - Modality: Text, Multimodal, Image, Audio, Video, Voice, Embeddings - what does this type of inference cost? - Channel: Model Developers, Cloud Marketplaces, Inference Platforms, Neoclouds - where should you buy? - Tier: Frontier, Budget, Mid, Reasoning - what's the premium for capability? - Special: Open-Source - how much cheaper is open-weight inference? Each index includes input, cached input, and output pricing per period. These are market-wide benchmarks, not individual vendor prices. Use them to understand where the market is and how it's moving. Fully public — available to all tiers. Examples: - "What's the current benchmark for text inference?" → index_category="Modality" - "Show me all AIPI indexes" → (no params) - "Neocloud pricing benchmark" → index_code="AIPI NCL GLB" - "Channel pricing comparison" → index_category="Channel" - "Open-source vs market pricing" → index_code="AIPI OSS GLB"
ATOM Inference Market KPIs — 9 cost and structure metrics derived from live pricing data across all tracked vendors: - Output Price Premium: how much more output tokens cost vs input - Caching Discount Rate: average discount for cached input pricing - Open Source Discount Rate: price gap between open-source and proprietary - Context Window Cost: price multiplier for 128K+ vs smaller context - Model Size Spread: price ratio between large and small models - Reasoning Premium: cost of reasoning models vs standard text - Platform Discount Rate: inference platforms vs buying direct - Neocloud Discount Rate: GPU-native providers vs model developers - Caching Availability: % of text models offering cached pricing These KPIs are available to all tiers — they demonstrate ATOM's market intelligence.
ATOM Model Intelligence — 6 capability and coverage metrics derived from the metadata behind every tracked model. Complements the pricing KPIs in get_kpis. Returns 6 metrics: - Reasoning Tier Share: % of general-purpose text models that are reasoning-tier - Long-Context Saturation: % of models shipping 128K+ context windows - Frontier Context Ceiling: context multiplier between top-decile and median models - Output Ceiling Spread: max output token multiplier between top-decile and median - Training Cutoff Lag: median months between model training cutoff and today - Vendor Modality Breadth: median number of modalities offered per vendor Read alongside pricing, these explain why a model is priced the way it is. Available to all tiers. Examples: - "How stale are AI models on average?" → Training Cutoff Lag - "What share of models support long context?" → Long-Context Saturation - "How rare are reasoning models?" → Reasoning Tier Share
List all AI inference vendors tracked by ATOM. Returns vendor name, country, region, and pricing page URL. Vendors span four channel types: Model Developers, Cloud Marketplaces, Inference Platforms, and Neoclouds. Optionally filter by region or country. Examples: - "List all vendors" → (no params) - "European AI vendors" → region="Europe" - "Chinese AI vendors" → country="China"
Atom Pricing Intelligence is an MCP server that lets any MCP‑compatible AI agent (e.g., Claude, GPT, Cursor) query live AI inference pricing data programmatically. Built on financial index methodology comparable to S&P Dow Jones, MSCI, and Bloomberg, it delivers the ATOM Inference Price Index (AIPI) — the first independent benchmark for the AI inference market. It is designed for developers, analysts, and infrastructure buyers who need transparent, deterministic pricing intelligence.
Connect via remote URL to Claude.ai or Claude Desktop (no install required), or use local stdio for Cursor, Windsurf, and similar clients. For the free tier no API key is needed; the Pro tier requires a subscription from a7om.com/mcp. You can also deploy your own instance on Railway using the provided environment variables.
It is the first independent benchmark for the AI inference market, built on financial index methodology, providing transparent and deterministic pricing intelligence across the global vendor landscape.
The server is built with TypeScript/Node.js, MCP SDK, Supabase, Express, and Zod. For local deployment, you need Node.js and a Supabase project with the provided environment variables.
The pricing data is stored in a Supabase (PostgreSQL) database and accessed via REST API. The hosted server is available at a Railway URL; local deployments connect to the same Supabase instance.
Transport can be either `stdio` (default) or `http`. The free tier requires no authentication; the Pro tier uses comma‑separated API keys set via the `ATOM_API_KEYS` environment variable.
The free tier provides full access to vendors, KPIs, model intelligence, and AIPI indexes, but only aggregated market stats, model counts and price ranges, specs‑only model detail, and summary vendor catalogs. Pro tier unlocks vendor‑level breakdowns, full granular SKU data, and per‑vendor pricing.
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