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AI Rate Card

REMOTE · AIRATECARD.COM

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

Available components

74 Trust /100

Last scanned (58 minutes ago)

Scores higher than 61% of remote servers

Reachable. Last reached 5 Nov 2026.

Category AI and Machine Learning

Trust breakdown (7 categories)

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. How we score → Why this is hard to score →

Endpoint Security80
Transport & Reachability100
Schema Quality & AI Usability76
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (good).Pass
  • 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. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management3
  • Stability observed for 1 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 13 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 14 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 5 Nov 26 0
    • Stability: unverified → 0.03 ▲ functional
  • 4 Nov 26 74

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 5 Nov 2026 · Probed https://airatecard.com/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=airatecard.com CN=YE2,O=Let's Encrypt,C=US 27 Sept 2026 26 Dec 2026 ECDSA 256 ECDSA-SHA384 69b8ff4c295de0d3b918958af4796e9dbf1
SANs: *.airatecard.com, airatecard.com
CN=YE2,O=Let's Encrypt,C=US (CA) CN=Root YE,O=ISRG,C=US 3 Sept 2025 2 Sept 2028 ECDSA 384 ECDSA-SHA384 4df3b15dd6c0784c507cd37b58e6f115
CN=Root YE,O=ISRG,C=US (CA) CN=ISRG Root X2,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 ECDSA-SHA384 872165fc34b6e5fba8add5b3705fb53a
CN=ISRG Root X2,O=Internet Security Research Group,C=US (CA) CN=ISRG Root X1,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 SHA256-RSA 6c8f1dc727c7117f7baf853ac980f9cd

Background: What to check on a remote MCP endpoint →

DNSSEC insecure

Validation of airatecard.com. — Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
com. present 19718 13 Verified
airatecard.com. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200
Header Value
strict-transport-security max-age=15552000; includeSubDomains
content-security-policy default-src 'self'; script-src 'self' 'inline-speculation-rules'; style-src 'self' 'unsafe-inline'; img-src 'self' data: https:; font-src 'self'; connect-src 'self'; object-src 'none'; base-uri 'self'; form-action 'self' https: http://127.0.0.1:* http://localhost:*; frame-ancestors 'none'
x-content-type-options nosniff
x-frame-options DENY
referrer-policy strict-origin-when-cross-origin
permissions-policy camera=(), microphone=(), geolocation=(), payment=(), usb=()

Background: How OAuth 2.1 works in the 2026 MCP spec →

Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://airatecard.com/mcp Verified 200
http (plaintext) http://airatecard.com/mcp HTTPS enforced 301 https://airatecard.com/mcp
MCP tools · 13 exposed · ~2,076 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
cheapest_for_workload ~329

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.

NameTypeReqDescription
categorystring–model type, llm by default
include_freeboolean–also free / promo offers (default false)
include_specialboolean–also batch, flex, priority, regional prices (default false)
input_modalitystring–the model must accept this input, e.g. image
input_tokensinteger–input tokens a month, e.g. 10000000
limitinteger–rows, 10 by default
min_contextinteger–context window needed, tokens, e.g. 128000
one_per_modelboolean–only the best offer of each model (default true)
output_tokensinteger–output tokens a month, e.g. 2000000
presetstring–chatbot | coding_agent | rag | summarization | long_context | vision | embedding_index | trial - fills tokens, min_context, category; your own values win
querystring–only models or providers matching these words, e.g. claude
toolsboolean–the model must support tool/function calling

No output schema declared.

No examples provided.

cheapest_models_by_task ~190

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.

NameTypeReqDescription
componentstring–input_tokens (default), output_tokens, or the task's own unit
ninteger–10 by default
scopestring–all (default), specialized (the task's own category) or multi/universal (qualifying llm models - the two names mean the same set, WP-0086)
taskstringyeswhat 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…

No output schema declared.

No examples provided.

cheapest_offers ~92

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.

NameTypeReqDescription
categorystring–model type, llm (text models) by default
limitinteger–rows, 10 by default

No output schema declared.

No examples provided.

compare_models ~115

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.

NameTypeReqDescription
modelsarrayyesmodel ids (e.g. openai/gpt-4o-mini, as model_id in search_offers rows) or names to search for

No output schema declared.

No examples provided.

estimate_cost ~139

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.

NameTypeReqDescription
cached_input_tokensinteger–of the input, tokens read from the prompt cache
input_tokensinteger–input tokens of the whole job, e.g. 1000000
modelstringyesmodel id or a name to search for
output_tokensinteger–output tokens of the whole job, e.g. 200000
requestsinteger–number of calls (for per-request prices)

No output schema declared.

No examples provided.

get_card ~151

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.

NameTypeReqDescription
card_idstringyesoffer:<provider>|<model>, model:<creator>/<model> or seller:<key>

No output schema declared.

No examples provided.

get_model_prices ~47

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

NameTypeReqDescription
modelstringyesmodel id or a name to search for

No output schema declared.

No examples provided.

list_articles ~59

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.

NameTypeReqDescription
langstring–language of the articles, en by default

No output schema declared.

No examples provided.

list_workload_presets ~38

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

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

median_price_by_task ~189

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.

NameTypeReqDescription
componentstring–input_tokens (default), output_tokens, or the task's own unit
ninteger–10 by default
scopestring–all (default), specialized (the task's own category) or multi/universal (qualifying llm models - the two names mean the same set, WP-0086)
taskstringyeswhat 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…

No output schema declared.

No examples provided.

most_expensive_models_by_task ~190

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.

NameTypeReqDescription
componentstring–input_tokens (default), output_tokens, or the task's own unit
ninteger–10 by default
scopestring–all (default), specialized (the task's own category) or multi/universal (qualifying llm models - the two names mean the same set, WP-0086)
taskstringyeswhat 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…

No output schema declared.

No examples provided.

search_offers ~285

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.

NameTypeReqDescription
categorystring–model type: llm (text models), embedding, image_generation, text_to_speech ...; none = every type
free_onlyboolean–only offers that cost nothing (default false)
input_modalitystring–e.g. text, image, audio
limitinteger–rows, 20 by default
max_input_pricenumber–USD per 1M input tokens, at most
min_contextinteger–context window in tokens, at least
multiboolean–also (or only, with no category) the multimodal offers that qualify (WP-0086)
querystring–words of the model, seller or display name
sortstring–order, price_input (cheapest input first) by default

No output schema declared.

No examples provided.

validate_provider_files ~252

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).

NameTypeReqDescription
domainstring–the provider's domain, e.g. example.ai
modelsstringyesthe models.yaml text
namestring–the provider's name

No output schema declared.

No examples provided.

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.

remote · airatecard.com

# add to Claude Code
claude mcp add --transport http com-airatecard-ai-rate-card 'https://airatecard.com/mcp'
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.