# AI Rate Card (remote · airatecard.com)

Daily-checked AI model API prices from 120+ providers: search, compare, cheapest, cost estimates.

- Trust score: 74/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- remote · `airatecard.com`: 74/100 (this document), [markdown](https://verifymcp.io/servers/com-airatecard-ai-rate-card/airatecard.md), [page](https://verifymcp.io/servers/com-airatecard-ai-rate-card/airatecard)

## Channel facts

- Endpoint: `https://airatecard.com/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.1`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, 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 2026-11-05.

- **Endpoint Security**: 80/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Nothing on it is marked destructive, but we can't show that an anonymous caller can only read: full credit needs the server to list at least one tool and every tool to be verifiably read-only. We use a best-effort check of tool names and descriptions to tell read-only tools from tools that change things, so some genuinely read-only tools may not get full credit. Names that start with a read verb (get, list, read, search and similar) and accurate readOnlyHint annotations help. Meet that to earn full credit, or require authorisation.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 76/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 2460 tokens (~189/item across 13 items; 13 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 3/100
  - Stability observed for 1 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.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 13 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 14 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the AI Rate Card MCP server?

AI Rate Card is a hosted endpoint at https://airatecard.com/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http com-airatecard-ai-rate-card 'https://airatecard.com/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "com-airatecard-ai-rate-card": {
      "url": "https://airatecard.com/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "com-airatecard-ai-rate-card": {
      "type": "http",
      "url": "https://airatecard.com/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.com-airatecard-ai-rate-card]
url = "https://airatecard.com/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-airatecard-ai-rate-card": {
      "type": "remote",
      "url": "https://airatecard.com/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-airatecard-ai-rate-card --url 'https://airatecard.com/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-airatecard-ai-rate-card:
    url: "https://airatecard.com/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "com-airatecard-ai-rate-card": {
      "Transport": "http",
      "Url": "https://airatecard.com/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add com-airatecard-ai-rate-card -t streamable-http -u 'https://airatecard.com/mcp'
```

### Other

```json
{
  "mcpServers": {
    "com-airatecard-ai-rate-card": {
      "type": "http",
      "url": "https://airatecard.com/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## 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.

### 2026-11-05 (score 74, 0)

- [functional improvement] Stability: unverified → 0.03

### 2026-11-04 (score 74)

First indexed and scored.

## MCP tools (13)

### `search_offers` (~285 tokens)

Search current AI model offers (one model at one provider = one offer) by words, model type and limits; priced offers first, doubtful prices after sane ones. Each row has offer_id, model_id, provider_id, prices in USD per 1M tokens (or per unit), card_url and a cite line. Next: get_card {"card_id": "offer:<offer_id>"} for one offer, get_model_prices for one model everywhere, estimate_cost / cheapest_for_workload for a cost.

Input parameters:

- `category` (string): model type: llm (text models), embedding, image_generation, text_to_speech ...; none = every type
- `free_only` (boolean): only offers that cost nothing (default false)
- `input_modality` (string): e.g. text, image, audio
- `limit` (integer): rows, 20 by default
- `max_input_price` (number): USD per 1M input tokens, at most
- `min_context` (integer): context window in tokens, at least
- `multi` (boolean): also (or only, with no category) the multimodal offers that qualify (WP-0086)
- `query` (string): words of the model, seller or display name
- `sort` (string): order, price_input (cheapest input first) by default

### `get_model_prices` (~47 tokens)

Every seller's current price of one model (an id, or a name to search for), cheapest input first.

Input parameters:

- `model` (string, required): model id or a name to search for

### `cheapest_offers` (~92 tokens)

The cheapest current offers (rows: one model at one provider) of one model type, by input price. For the cheapest MODELS of a job (one row per model) use cheapest_models_by_task; for a monthly workload use cheapest_for_workload.

Input parameters:

- `category` (string): model type, llm (text models) by default
- `limit` (integer): rows, 10 by default

### `compare_models` (~115 tokens)

2 to 5 models side by side: the best current offer of each and, for up to 4, every field compared (lowest and median input/output price, context, max output, providers, regions, a 1M-in/200k-out workload cost), who wins by how many percent, providers selling all, and summary sentences.

Input parameters:

- `models` (array, required): model ids (e.g. openai/gpt-4o-mini, as model_id in search_offers rows) or names to search for

### `estimate_cost` (~139 tokens)

The cost of a workload (input, output and cached input tokens, number of requests) at every current provider of one model, cheapest first, in USD - what the same job costs where.

Input parameters:

- `cached_input_tokens` (integer): of the input, tokens read from the prompt cache
- `input_tokens` (integer): input tokens of the whole job, e.g. 1000000
- `model` (string, required): model id or a name to search for
- `output_tokens` (integer): output tokens of the whole job, e.g. 200000
- `requests` (integer): number of calls (for per-request prices)

### `get_card` (~151 tokens)

One card with its citation. card_id is '<kind>:<key>': offer:<provider>|<model id as the provider writes it> (e.g. offer:anthropic|claude-opus-4), model:<creator>/<model> (e.g. model:anthropic/claude-opus-4), seller:<provider key> (e.g. seller:anthropic). Ids come from search_offers (offer_id, model_id, provider_id) and from the card_url of every result. Works for every seller, a hidden test seller too.

Input parameters:

- `card_id` (string, required): offer:<provider>|<model>, model:<creator>/<model> or seller:<key>

### `validate_provider_files` (~252 tokens)

For a provider (seller) joining the catalog: check a models.yaml before putting it online - the same check as the wizard and POST /v1/provider/validate. Give the file's text in `models` (YAML, or the same structure as JSON text); `domain` (the provider's site) makes the model_page checks exact. Returns ok, the problems (file, line, model, path, value, code, message, hint - fix each and call again), the catalog's preview of the models and next_action. No account needed for this check. Publishing needs a signed-in person: the provider_* tools (provider_start -> provider_verify_domain -> provider_check_files -> provider_publish) are on the account server /mcp/account (OAuth sign-in, scope provider), not on this public server; or the wizard at /join, or POST /v1/provider/applications. Templates: /static/templates/models.min.yaml (required fields only) and models.yaml (every field with hints).

Input parameters:

- `domain` (string): the provider's domain, e.g. example.ai
- `models` (string, required): the models.yaml text
- `name` (string): the provider's name

### `cheapest_for_workload` (~329 tokens)

The cheapest offers for a whole monthly workload, ranked by monthly cost in USD: give a preset (a typical job; see list_workload_presets) and/or your own tokens a month. Best offer of each model; free promos and batch/flex/priority/regional prices left out unless asked. Each row: monthly_cost_usd, prices, context, checked_at, card_url and a ready cite line.

Input parameters:

- `category` (string): model type, llm by default
- `include_free` (boolean): also free / promo offers (default false)
- `include_special` (boolean): also batch, flex, priority, regional prices (default false)
- `input_modality` (string): the model must accept this input, e.g. image
- `input_tokens` (integer): input tokens a month, e.g. 10000000
- `limit` (integer): rows, 10 by default
- `min_context` (integer): context window needed, tokens, e.g. 128000
- `one_per_model` (boolean): only the best offer of each model (default true)
- `output_tokens` (integer): output tokens a month, e.g. 2000000
- `preset` (string): chatbot | coding_agent | rag | summarization | long_context | vision | embedding_index | trial - fills tokens, min_context, category; your own values win
- `query` (string): only models or providers matching these words, e.g. claude
- `tools` (boolean): the model must support tool/function calling

### `list_workload_presets` (~38 tokens)

The ready-made workloads of cheapest_for_workload: name, what job it is, tokens a month, context needed, model type.

### `list_articles` (~59 tokens)

AI Rate Card's articles on AI model prices (the cheapest models by task, price moves, costs), newest first, with their links - to quote or point a reader to.

Input parameters:

- `lang` (string): language of the articles, en by default

### `cheapest_models_by_task` (~190 tokens)

The n cheapest MODELS for a job (task): each model counted once at its own lowest current price (input tokens by default). One row per model with that price, where it is and card_url.

Input parameters:

- `component` (string): input_tokens (default), output_tokens, or the task's own unit
- `n` (integer): 10 by default
- `scope` (string): all (default), specialized (the task's own category) or multi/universal (qualifying llm models - the two names mean the same set, WP-0086)
- `task` (string, required): what the buyer wants done: text (chat/LLM), vision, image, video, tts (speech from text), stt (text from speech), embedding, rerank, moderation - a job, not a model type (search_offers' category is t…

### `most_expensive_models_by_task` (~190 tokens)

The n most expensive MODELS for a job (task): each model counted once at its own lowest current price, highest first - the top of the market. Same arguments as cheapest_models_by_task.

Input parameters:

- `component` (string): input_tokens (default), output_tokens, or the task's own unit
- `n` (integer): 10 by default
- `scope` (string): all (default), specialized (the task's own category) or multi/universal (qualifying llm models - the two names mean the same set, WP-0086)
- `task` (string, required): what the buyer wants done: text (chat/LLM), vision, image, video, tts (speech from text), stt (text from speech), embedding, rerank, moderation - a job, not a model type (search_offers' category is t…

### `median_price_by_task` (~189 tokens)

The typical (median) current price of a job (task) across models, and the n models closest to it - what a normal price for this job is. Same arguments as cheapest_models_by_task.

Input parameters:

- `component` (string): input_tokens (default), output_tokens, or the task's own unit
- `n` (integer): 10 by default
- `scope` (string): all (default), specialized (the task's own category) or multi/universal (qualifying llm models - the two names mean the same set, WP-0086)
- `task` (string, required): what the buyer wants done: text (chat/LLM), vision, image, video, tts (speech from text), stt (text from speech), embedding, rerank, moderation - a job, not a model type (search_offers' category is t…

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-airatecard-ai-rate-card/airatecard#diagnostics

## Score history

- 2026-11-05: 74
- 2026-11-04: 74

## Common questions

### What is the AI Rate Card MCP server?

AI Rate Card is an MCP server listed in the public MCP registry as com.airatecard/ai-rate-card. Daily-checked AI model API prices from 120+ providers: search, compare, cheapest, cost estimates. This page covers its hosted endpoint (https://airatecard.com/mcp).

### Is the AI Rate Card MCP server safe to use?

AI Rate Card scores 74 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the AI Rate Card MCP server expose?

AI Rate Card exposes 13 tools: search_offers, get_model_prices, cheapest_offers, compare_models, estimate_cost, and 8 more. Their descriptions and schemas cost roughly 2,076 tokens of context every time the server is loaded.

### Does the AI Rate Card MCP server require authentication?

No. We connected to AI Rate Card without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the AI Rate Card MCP server still maintained?

AI Rate Card is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What did VerifyMCP test on the AI Rate Card MCP server?

VerifyMCP ran 13 checks on AI Rate Card, covering TLS certificate, Authorization, HTTPS, HSTS header and 9 more. Supply Chain Security and Provenance & Transparency do not apply to a hosted endpoint, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.

## Links

- Remote endpoint: https://airatecard.com/mcp
- Website: https://airatecard.com/docs
- Changelog RSS feed: https://verifymcp.io/servers/com-airatecard-ai-rate-card/airatecard.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-airatecard-ai-rate-card/airatecard/changelog.json
- Trust report (JSON): https://verifymcp.io/servers/com-airatecard-ai-rate-card/airatecard.json
- HTML version of this page: https://verifymcp.io/servers/com-airatecard-ai-rate-card/airatecard