infercpi
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@infercpicompare what open vs closed models cost per million tokens"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 |
| Last value of every series, plus the weekly editorial note |
| Catalogue of every series: point count, dates, method string, URL |
| Full history: |
| Every model priced this week: input, output and blended $/1M, context, Epoch ECI, open or closed |
| Launches, price cuts, increases and removals since Sep 2023 |
| Our daily speed run: time to first token, tokens per second |
| Tokens routed through OpenRouter per week, by lab and region |
| 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/.
Related MCP server: InferenceIndexer MCP Server
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 CodeClaude.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 :8765Claude 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.
This server cannot be deployed
Maintenance
Related MCP Connectors
Read-only lookups of public AI agent pricing, free plans and source links. No API key.
API Tool Calls: Home cost planners, proofreading, QR and barcodes, page to Markdown, SEO checks and recalls. Free agent tools: 20 calls/day per IP, no key.
AI inference pricing for agents: live and historical model prices, provider comparison.
Look up, compare and track AI model API prices from an AI assistant. No sign-in needed.
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