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ATOM Pricing Intelligence

ATOM Pricing Intelligence

@a7om-aiData & AnalyticsTypeScriptUpdated 3w ago

The Global Price Benchmark for AI Inference. 1,600+ SKUs, 40+ vendors, 14 price indexes.

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ATOM

ATOM MCP Server

The Global Price Benchmark for AI Inference, delivered as a native tool for AI agents.
Independent pricing intelligence for developers, analysts, and infrastructure buyers. Transparent methodology, deterministic indexing, weekly market intelligence across the global AI inference market.

Website · About ATOM · Methodology · ATOM MCP Pro


What This Is

ATOM MCP Server lets any MCP-compatible AI agent (Claude, GPT, Cursor, Windsurf, VS Code Copilot) query live AI inference pricing data programmatically. Built on financial index methodology comparable to S&P Dow Jones, MSCI, and Bloomberg, the ATOM Inference Price Index (AIPI) is the first independent benchmark for the AI inference market.

Ask your AI assistant a question like "What's the cheapest way to run GPT-4o?" and it calls ATOM's tools behind the scenes, returning a data-backed answer pulled from live coverage across the global vendor landscape.


AIPI Indexes

The AIPI index family spans four categories, all calculated weekly using chained matched-model methodology to eliminate composition bias:

CategoryExamplesWhat It Answers
ModalityText, Multimodal, Image, Audio, Video, VoiceWhat does this type of inference cost?
ChannelModel Developers, Cloud Marketplaces, Inference Platforms, NeocloudsWhere should you buy: direct, marketplace, platform, or neocloud?
TierFrontier, Budget, Mid-Tier, ReasoningWhat is the premium for capability?
SpecialOpen-SourceHow much cheaper is open-weight inference?

All indexes are global (GLB) and reported across three pricing directions: input, cached input, output.


Tools

Two complementary intelligence layers. Pricing tells you what inference costs; Model Intelligence tells you what you are paying for.

ToolTierDescription
list_vendorsFreeAll tracked vendors with country, region, channel type, and pricing page URLs
get_kpisFree9 pricing KPIs: output premium, caching discount, open-source discount, context window cost, model size spread, reasoning premium, platform discount, neocloud discount, caching availability
get_model_intelligenceFree6 capability KPIs from model metadata: reasoning tier share, long-context saturation, frontier context ceiling, output ceiling spread, training cutoff lag, vendor modality breadth
get_index_benchmarksFreeAIPI price benchmarks across all 15 indexes
get_market_statsTieredAggregate market intelligence: medians, quartiles, distributions, modality breakdown
search_modelsTieredMulti-filter search: modality, vendor, creator, open-source, price range, context window, parameters
get_model_detailTieredFull specs and pricing across all vendors for a single model
compare_pricesTieredCross-vendor price comparison for a model or model family
get_vendor_catalogTieredComplete catalog for a specific vendor

Pricing Tiers

ATOM MCP (Free)ATOM MCP Pro
Vendors, KPIs, Model Intelligence, AIPI indexesFull dataFull data
Market statsAggregates onlyVendor-level breakdown
Model search and comparisonCounts and price rangesFull granular SKU data
Model detailSpecs onlyPer-vendor pricing
Vendor catalogSummary onlyFull SKU listing

Free tier (no API key): enough to understand the market through counts, ranges, distributions, benchmarks, and capability metrics.

ATOM MCP Pro: full granular data across every vendor, model, price, and spec. Subscribe at a7om.com/mcp.


Quick Start

Option 1: Remote URL for Claude.ai and Claude Desktop (recommended)

No install required. Connect directly to ATOM's hosted server.

Claude.ai (web): Settings → Connectors → Add custom connector

Name: ATOM Pricing Intelligence
URL:  https://atom-mcp-server-production.up.railway.app/mcp

Claude Desktop: Settings → Developer → Edit Config

{
  "mcpServers": {
    "atom-pricing": {
      "url": "https://atom-mcp-server-production.up.railway.app/mcp"
    }
  }
}

Note: Remote URL support requires a recent Claude Desktop version. If it does not work, use the npx method below.

Claude Desktop (via npx proxy):

{
  "mcpServers": {
    "atom-pricing": {
      "command": "npx",
      "args": ["mcp-remote", "https://atom-mcp-server-production.up.railway.app/mcp"]
    }
  }
}

Option 2: Local (stdio) for Cursor, Windsurf, and similar clients

git clone https://github.com/A7OM-AI/atom-mcp-server.git
cd atom-mcp-server
npm install && npm run build

Add to your MCP client config:

{
  "mcpServers": {
    "atom-pricing": {
      "command": "node",
      "args": ["/path/to/atom-mcp-server/dist/index.js"],
      "env": {
        "SUPABASE_URL": "https://jonncmzxvxzwyaznokba.supabase.co",
        "SUPABASE_ANON_KEY": "your-anon-key"
      }
    }
  }
}

Option 3: Deploy your own (Railway)

Deploy on Railway

Set environment variables in Railway dashboard:

  • SUPABASE_URL
  • SUPABASE_ANON_KEY
  • ATOM_API_KEYS (comma-separated, for paid tier validation)
  • TRANSPORT=http

Example Queries

Once connected, ask your AI assistant in natural language:

  • "What's the cheapest way to run GPT-4o?"
  • "Compare Claude Sonnet 4.5 pricing across all vendors"
  • "Find open-source text models under $0.50 per million tokens"
  • "Show me Google's full model catalog"
  • "What are the AIPI benchmark prices for text inference?"
  • "How do neocloud prices compare to cloud marketplaces?"
  • "How much cheaper is open-source inference?"
  • "How stale is the median AI model's training data?"
  • "What share of models ship with long context, and how rare are reasoning models?"
  • "Give me a market overview of AI inference pricing"

Environment Variables

VariableRequiredDescription
SUPABASE_URLYesSupabase project URL
SUPABASE_ANON_KEYYesSupabase anonymous/public key
ATOM_API_KEYSNoComma-separated valid API keys for paid tier
TRANSPORTNostdio (default) or http
PORTNoHTTP port (default 3000)

Tech Stack

  • TypeScript / Node.js
  • MCP SDK (@modelcontextprotocol/sdk)
  • Supabase (PostgreSQL) via REST API
  • Express (HTTP transport)
  • Zod (schema validation)

About ATOM

The Global Price Benchmark for AI Inference. Independent pricing intelligence for developers, analysts, and infrastructure buyers. Transparent methodology, deterministic indexing, weekly market intelligence across the global AI inference market.

ATOM was founded in 2025 by Stamos Kanellakis. The platform is built on financial index methodology comparable to S&P Dow Jones, MSCI, and Bloomberg, and applies that discipline to a market that previously had no pricing benchmark of its own.

Products: ATOM MCP · ATOM Terminal · ATOM Feed


License

MIT


ATOM · The Global Price Benchmark for AI Inference.