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InferCPI

InferCPI

Remote
infercpi.comData & Analytics0Updated 1d ago

About InferCPI

InferCPI publishes data on AI inference prices and costs for analysts and agents. Its free API and MCP server cover model pricing, capability-adjusted costs, hosting, speed, and cost per task.

Key features

  1. 01Read inference price indexes
  2. 02Compare model prices and capabilities
  3. 03Review open and closed models
  4. 04Explore hosting and self-hosting costs
  5. 05Check speed and cost per task

Use cases

  1. 01Compare model prices before selection
  2. 02Track price changes over time
  3. 03Assess hosted versus self-hosted costs
  4. 04Estimate inference cost for a task

MCP support

The MCP server provides ten read-only tools over the InferCPI API, hosted at https://infercpi.com/mcp with no key required. It can also be run locally.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://infercpi.com/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

InferCPI API

InferCPI tracks what AI inference costs: list prices, what buyers actually pay, the cost of a fixed level of capability, open vs closed models, third-party hosts, self-hosting, and cost per completed task. Site: https://infercpi.com.

This repo holds the public API docs, examples and the MCP server. The data is free, needs no key, and is licensed CC BY 4.0: cite as InferCPI, infercpi.com.

API

Static JSON at https://infercpi.com/v1/. Full reference: https://infercpi.com/api.html.

FileWhat
latest.jsonLast value of every series, plus the weekly editorial note
index.jsonCatalogue of every series: point count, dates, method string, URL
series/<signal>/<key>.jsonFull history: points: [[unix_ts, value], ...] and method
basket.jsonEvery model priced this week: input, output and blended $/1M, context, Epoch ECI, open or closed
events.jsonLaunches, price cuts, increases and removals since Sep 2023
speed.jsonOur daily speed run: time to first token, tokens per second
token_mix.jsonTokens routed through OpenRouter per week, by lab and region
capex.jsonHyperscaler capex, chip and cloud revenue by quarter (SEC filings)
curl -s https://infercpi.com/v1/latest.json | jq '.latest["weighted_index/paid_usd_1m"]'

More in examples/.

MCP server

mcp_server.py gives agents ten read-only tools over the API: index_latest, index_series, index_catalogue, basket, model_price, events, speed, open_vs_closed, self_hosting, cost_per_task.

Hosted, no key: https://infercpi.com/mcp (streamable HTTP).

claude mcp add --transport http infercpi https://infercpi.com/mcp   # Claude Code

Claude.ai and Claude Desktop: Settings → Connectors → Add custom connector, paste the URL.

Or run it yourself:

mkdir -p ~/.local/share/infercpi
curl -so ~/.local/share/infercpi/mcp_server.py https://raw.githubusercontent.com/Infer-CPI/api/main/mcp_server.py
pip install mcp                                       # mcp 1.x or 2.x both work
claude mcp add infercpi -s user -- python3 ~/.local/share/infercpi/mcp_server.py   # Claude Code
python3 ~/.local/share/infercpi/mcp_server.py --http  # or: streamable HTTP on :8765

Claude Desktop (claude_desktop_config.json):

{ "mcpServers": { "infercpi": { "command": "python3", "args": ["/home/YOU/.local/share/infercpi/mcp_server.py"] } } }

It reads https://infercpi.com by default; set INFERCPI_BASE to point elsewhere.

Method and sources

How every series is built: https://infercpi.com/methodology.html. Inputs: LiteLLM and pydantic/genai-prices (MIT), Epoch AI Capabilities Index (CC BY 4.0), OpenRouter rankings (CC BY 4.0), SEC filings (public domain). Speed and cost per task are our own measurements.

Licence

Code in this repo: MIT. Index data: CC BY 4.0. Questions, corrections or a series you need: open an issue.

Comments

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