# ATOM Pricing Intelligence (npm · atom-mcp-server)

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

- Trust score: 68/100 (medium)
- Change this week: +43
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `atom-mcp-server-production.up.railway.app`: 23/100, [markdown](https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server-production.md), [page](https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server-production)
- npm · `atom-mcp-server`: 68/100 (this document), [markdown](https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server.md), [page](https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server)

## Channel facts

- Registry: `npm`
- Package: `atom-mcp-server`
- Version: `1.1.2`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Supply Chain Security**: 87/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (95 of 96), so this covers what we could see, not the whole tree.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (95 of 96), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 149 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 67/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1738 tokens (~217/item across 8 items; 8 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add a7om-ai-atom-mcp-server -- npx -y atom-mcp-server
```

### Codex

```bash
codex mcp add a7om-ai-atom-mcp-server -- npx -y atom-mcp-server
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "a7om-ai-atom-mcp-server": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "atom-mcp-server"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add a7om-ai-atom-mcp-server --command npx --arg -y --arg atom-mcp-server
```

### Hermes

```yaml
mcp_servers:
  a7om-ai-atom-mcp-server:
    command: "npx"
    args: ["-y", "atom-mcp-server"]
```

### Other

```json
{
  "mcpServers": {
    "a7om-ai-atom-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "atom-mcp-server"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-02 (score 67, +62)

- [security regression] Provenance: unverified → fail
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Install scripts: unverified → pass
- [security improvement] Malware scan: unverified → pass
- [functional improvement] Stability: unverified → 0.23
- [functional improvement] MCP protocol: unverified → pass
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] License: unverified → pass
- [functional improvement] Tool coverage: unverified → 100
- [functional] Licence: MIT

### 2026-08-01 (score 5, −29)

- [security] Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.
- [functional regression] Capabilities: pass → unverified
- [functional regression] Tool coverage: 100 → unverified

### 2026-07-31 (score 34, −26)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 60, −18)

- [security regression] Malware scan: pass → unverified

### 2026-07-28 (score 78, +53)

- [security regression] Provenance: unverified → fail
- [security improvement] Install scripts: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] Tool coverage: unverified → 100
- [functional improvement] License: unverified → pass
- [functional] First check of Schema quality: fail
- [functional] First check of Schema quality: excellent
- [functional] First check of Schema quality: fail
- [functional] First check of Tool coverage: 100
- [functional] Licence: MIT

### 2026-07-27 (score 25)

First indexed and scored.

## MCP tools (8)

### `search_models` (~385 tokens)

Search AI Models

Search and filter AI inference models across 40+ vendors and 1,600+ 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

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).
- `creator` (string): Filter by model creator/developer
- `direction` (string): Filter by pricing direction
- `limit` (integer): Maximum results to return (default 20)
- `max_price` (number): Maximum normalized price (USD per unit)
- `min_context_window` (integer): Minimum context window in tokens
- `min_parameter_count` (string): Minimum parameter count, e.g. '7B', '70B'
- `modality` (string): Filter by modality: Text, Image, Audio, Video, Voice, Multimodal, Embedding
- `model_family` (string): Filter by model family, e.g. 'GPT-4o', 'Claude 3.5'
- `offset` (integer): Offset for pagination
- `open_source` (string): Filter by open-source status: 'true' or 'false'
- `vendor` (string): Filter by vendor name, e.g. 'OpenAI', 'Anthropic'

### `get_model_detail` (~176 tokens)

Get Model Details

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"

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).
- `model_name` (string, required): Model name to look up, e.g. 'GPT-4o', 'Claude Sonnet 4.5', 'Llama 3.1 70B'

### `compare_prices` (~248 tokens)

Compare Prices Across Vendors

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"

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).
- `direction` (string): Filter by pricing direction
- `limit` (integer): Maximum results (default 50)
- `modality` (string): Filter by modality: Text, Image, Audio, etc.
- `model_family` (string): Model family to compare, e.g. 'GPT-4o', 'Claude 3.5'
- `model_name` (string): Model name to compare prices for, e.g. 'GPT-4o', 'Llama 3.1 70B'

### `get_vendor_catalog` (~201 tokens)

Get Vendor Catalog

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"

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).
- `direction` (string): Optionally filter by pricing direction
- `limit` (integer): Maximum results (default 50)
- `modality` (string): Optionally filter by modality: Text, Image, Audio, Video, Voice, Multimodal
- `vendor` (string, required): Vendor name, e.g. 'OpenAI', 'Together AI', 'Amazon Bedrock'

### `get_market_stats` (~139 tokens)

Get Market Statistics

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"

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).
- `modality` (string): Optionally focus on a specific modality: Text, Image, Audio, Video, etc.

### `get_index_benchmarks` (~273 tokens)

Get AIPI Index Benchmarks

AIPI (ATOM Inference Price Index) — chained matched-model price benchmarks for AI inference.

Returns benchmark prices across index families (Text, Image, Audio, Video, Multimodal, Composite) with input, cached, 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="Text"
  \- "Show me all AIPI indexes" → (no params)
  \- "AIPI-TXT-GLB history" → index_code="AIPI-TXT-GLB"

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).
- `index_category` (string): Filter by index category, e.g. 'Text', 'Image', 'Audio', 'Video', 'Multimodal', 'Composite'
- `index_code` (string): Filter by specific AIPI index code, e.g. 'AIPI-TXT-GLB', 'AIPI-IMG-GLB'. Omit to see all indexes.
- `limit` (integer): Maximum results to return (default 25)

### `get_kpis` (~159 tokens)

Get Market KPIs

ATOM Inference Price Index (AIPI) market-level KPIs.

Returns 6 key performance indicators derived from 1,600+ SKUs:
\- Output Premium: how much more output tokens cost vs input
\- Caching Savings: average discount for cached input pricing
\- Open Source Advantage: price difference between open-source and proprietary
\- Context Cost Curve: price multiplier for larger context windows
\- Caching Availability: % of models offering cached pricing
\- Size Spread: price ratio between largest and smallest models

These KPIs are available to all tiers — they demonstrate ATOM's market intelligence.

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).

### `list_vendors` (~157 tokens)

List All Vendors

List all 41 AI inference vendors tracked by ATOM.

Returns vendor name, country, region, and pricing page URL. Optionally filter by region or country.

Examples:
  \- "List all vendors" → (no params)
  \- "European AI vendors" → region="Europe"
  \- "Chinese AI vendors" → country="China"

Input parameters:

- `_atom_api_key` (string): Your ATOM API key for full access. Omit for free tier (redacted data).
- `country` (string): Optionally filter by country, e.g. 'United States', 'China', 'France'
- `region` (string): Optionally filter by region: 'North America', 'Europe', 'Asia', etc.

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server#diagnostics

## Score history

- 2026-08-03: 68
- 2026-08-02: 67
- 2026-08-01: 5
- 2026-07-31: 34
- 2026-07-30: 60
- 2026-07-29: 78
- 2026-07-28: 78
- 2026-07-27: 25

## Links

- npm package: https://www.npmjs.com/package/atom-mcp-server
- Socket report: https://socket.dev/npm/package/atom-mcp-server
- Repository: https://github.com/A7OM-AI/atom-mcp-server
- Website: https://a7om.com/mcp
- Changelog RSS feed: https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server/changelog.json
- HTML version of this page: https://verifymcp.io/servers/a7om-ai-atom-mcp-server/atom-mcp-server