AI Rate Card MCP server

• Registry namecom.airatecard/ai-rate-cardverified in the MCP registry

The registry name sits under airatecard.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.

• Stateanswerschecked 2026-11-04
• Tools13
• Server calls itselfai-rate-card
• Server version1
• Protocol version2025-06-18

On 2026-11-04 the server answered initialize and tools/list without a sign-in. First answer in 542 ms.

• Whether its tools do the product's job has not been judged yet.
• Checked on 1 of the 7 days it takes to judge reliability.

Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.

• INITE MCP scoreafter a weeka score needs 7 daily checks: 1 so far
• Answeredmeasuring1 of the 7 daily checks it takes to print a share
• Median first answer538 ms
• Space in an agent's context≈ 3,019 tokensthe definitions of all its tools (13), which an agent carries on every turn
• Tool definitionsA · 100 of 100
• Typed results0 of 13 toolsdeclared outputSchema: results come typed, read once

• Every tool passes all six checks.

A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →

• search_offers

  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…

• get_model_prices

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

• cheapest

  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; for a monthly workload use cheapest_for_workload.

• compare_models

  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…

• estimate_cost

  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.

• get_card

  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…

• validate_provider_files

  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`…

• cheapest_for_workload

  The cheapest offers for a whole monthly workload, ranked by monthly cost in USD: give a preset (a typical job; see workload_presets) and/or your own tokens a month. Best offer of each model; free promos and batch/flex/priority/regional…

• workload_presets

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

• list_articles

  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.

• cheapest_models

  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.

• dearest_models

  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.

• median_models

  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.