InferCPI MCP

Latest value of every index series (list-price chained/composition/hedonic, usage-weighted paid price, Törnqvist, OpenRouter shares, TPI replica) with dates, the latest editorial note, and the licence/attribution line. Start here.

{
  "type": "object",
  "title": "index_latestArguments",
  "properties": {}
}

Full weekly history of one series as [[unix_ts, value], ...] plus its method string. signal: price_index | weighted_index | or_rankings | implied_margin | self_host | task_cost | hf_downloads | gpu_spot | gpu_neocloud | aws_gpu | speed | hyperscaler_capex | seller_revenue | cloud_revenue | token_price ... key: see index_catalogue. since: optional ISO date to cut the history.

{
  "type": "object",
  "title": "index_seriesArguments",
  "required": [
    "signal",
    "key"
  ],
  "properties": {
    "key": {
      "type": "string",
      "title": "Key"
    },
    "since": {
      "type": "string",
      "title": "Since",
      "default": ""
    },
    "signal": {
      "type": "string",
      "title": "Signal"
    }
  }
}

Every series the index publishes: signal/key, point count, first and last date, method string.

{
  "type": "object",
  "title": "index_catalogueArguments",
  "properties": {}
}

Every model priced in this week's list-price index: provider, blended $/1M (0.75 in + 0.25 out), Epoch capability score where matched.

{
  "type": "object",
  "title": "basketArguments",
  "properties": {}
}

Priced events in first-party price lists, newest first: launch, price_cut, price_increase, removed, each with key, provider, old/new blended $/1M and pct. since: ISO date; kind: filter to one kind.

{
  "type": "object",
  "title": "eventsArguments",
  "properties": {
    "kind": {
      "type": "string",
      "title": "Kind",
      "default": ""
    },
    "since": {
      "type": "string",
      "title": "Since",
      "default": ""
    }
  }
}

Latest daily speed run, measured by the index: per model and route (openrouter default routing, openrouter_pinned to the first-party host, anthropic and openai direct), median time to first token (ms), visible output tokens per second, host that served it. Same prompt every day.

{
  "type": "object",
  "title": "speedArguments",
  "properties": {}
}

Blended list $/1M for one model by any common name ('Claude Opus 5.5', 'anthropic/claude-opus-5.5', 'gpt-5.5'); matches by the index's name normaliser and returns every basket entry that matches.

{
  "type": "object",
  "title": "model_priceArguments",
  "required": [
    "name"
  ],
  "properties": {
    "name": {
      "type": "string",
      "title": "Name"
    }
  }
}

Cheapest blended $/1M at each capability level (Epoch ECI 130/145/160) for closed models, open models at their lab's price and open models at the cheapest third-party host; the open discount; DeepSeek's floor lift (cheapest price without DeepSeek / cheapest overall, at lab and at host prices); and the host discount per open model (lab price / cheapest host).

{
  "type": "object",
  "title": "open_vs_closedArguments",
  "properties": {}
}

What it costs per 1M tokens to leave the APIs: desk boxes (Mac Studio lease, RTX 5090 bought) at full and 25% duty, H100 rented by source (Vast, AWS, RunPod, CoreWeave, Lambda, Nebius) and owned, against the API price of the same open model and of the cheapest closed model at equal capability; break-even volume and how far hardware cost must fall. Plus posted GPU-hour prices and Hugging Face download counts.

{
  "type": "object",
  "title": "self_hostingArguments",
  "properties": {}
}

Monthly measurement: dollars and tokens per completed task for the most-used models (fixed 8-task suite via OpenRouter at default settings, charged cost), reasoning share of output tokens, accuracy, and medians.

{
  "type": "object",
  "title": "cost_per_taskArguments",
  "properties": {}
}