mcp server
AI Pricing Hub
Source-backed AI model pricing, rankings, history, and benchmark data.
Description as published by the maintainer. Source
- version 1.0.0
- archived
- evaluation
archived — The linked repository returns 404. It was deleted, renamed or made private. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
What this server can do
11 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
benchmark_lookup(limit, cursor, model_id, provider, benchmark_id)- Find sourced benchmark rows by model, provider, or benchmark ID.
calculate_cost(model_id, requests, input_tokens, output_tokens, cached_input_tokens)- Estimate cost from model pricing and token volumes.
compare_models(model_ids)- Compare pricing, context, and sourced benchmarks for model IDs.
find_best_value(limit, cursor, provider, benchmark_id)- Rank models by available benchmark signal per listed token price.
find_cheapest(limit, cursor, provider, workload)- Find cheapest models by combined listed input plus output token price.
latest_changes(type, limit, cursor, provider)- Return recent model launches, removals, and pricing changes.
pricing_history(model_id)- Return historical pricing snapshots for a model ID.
provider_summary(provider)- Summarize model count, prices, benchmarks, and changes for a provider.
recommend_model(limit, budget, provider, workload, min_context_tokens)- Recommend models for a workload using price, context, and benchmark evidence.
search_models(limit, query, cursor, provider, workload, max_combined_price, min_context_tokens)- Search the pricing catalog with provider, workload, context, and price filters.
search_news(limit, query, cursor, source, language)- Search AI Pricing Hub news items.
Last successful function declaration observed on . Source: https://aipricinghub.com/mcp/rpc. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://aipricinghub.com/mcp/rpc.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-13 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| First listed in the MCP Registry | 2026-07-13 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | not_found | GitHub returned 404 for the repository the maintainer listed. The project was deleted, renamed or made private, so the listing points at nothing. | as of fetch | GitHub | |
| mcp tools declared | 11 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | aipricinghub.com | |
| mcp endpoint status | ok | The server listed 11 functions when asked. | as of probe | aipricinghub.com |
Where to get it
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json