InferCPI
AI inference price index: token prices, cost per capability, open vs closed, hosts, cost per task.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
claude mcp add --transport http infercpi 'https://infercpi.com/mcp'
{
"mcpServers": {
"infercpi": {
"type": "http",
"url": "https://infercpi.com/mcp"
}
}
}
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
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**.
| File | What |
|---|---|
latest.json | Last value of every series, plus the weekly editorial note |
index.json | Catalogue of every series: point count, dates, method string, URL |
series/<signal>/<key>.json | Full history: points: [[unix_ts, value], ...] and method |
basket.json | Every model priced this week: input, output and blended $/1M, context, Epoch ECI, open or closed |
events.json | Launches, price cuts, increases and removals since Sep 2023 |
speed.json | Our daily speed run: time to first token, tokens per second |
token_mix.json | Tokens routed through OpenRouter per week, by lab and region |
capex.json | Hyperscaler 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.
Frequently asked questions
What is InferCPI?
AI inference price index: token prices, cost per capability, open vs closed, hosts, cost per task.
How do I install InferCPI?
It runs as a remote server. In Claude Code: claude mcp add --transport http infercpi 'https://infercpi.com/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.
Does InferCPI need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is InferCPI open source?
Its code is public on GitHub, but the repository does not declare a standard license.
Who maintains InferCPI?
It is published by Infer-CPI. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.