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name: tokenomics description: Get fresh, live LLM pricing and cost estimates via the tokenomics CLI or MCP server.

tokenomics — live LLM pricing for agents

Prices come live from the models.dev catalog (thousands of models across 140+ providers). There is no local database and no cache to refresh — every call reflects current data.

Units (read this first)

• All token prices are USD per 1,000,000 tokens. A value of 2.5 means $2.50 per 1M tokens.
• estimate/estimate_cost take raw token counts (e.g. 1000000), not millions.
• output_per_mtok: null means the model is non-generative (embeddings/rerankers); output tokens cost $0.

Rules

• Use --output json (or rely on the default: JSON whenever output is piped) and parse it.
• Add --fields a,b,c to every search to keep responses small (masks the rows under models).
• Resolve real model ids with search before get/estimate. Model ids are provider/model, e.g. openai/gpt-4o.
• For "which is cheaper for my workload", use compare / compare_models — it does the math; don't compute prices yourself.
• Model and provider ids are plain identifiers: no ?, #, %, /-prefixed paths, or query params.
• On MODEL_NOT_FOUND, read details.suggestions or run search; do not invent ids.

CLI quickstart

tokenomics search "gpt" --max-input 1 --fields model_id,pricing --output json
tokenomics get openai/gpt-4o
tokenomics estimate openai/gpt-4o --input-tokens 1000000 --output-tokens 200000 --requests 10
tokenomics compare --models openai/gpt-4o,google/gemini-2.5-flash --input-tokens 1000000 --output-tokens 500000
tokenomics providers
tokenomics schema estimate   # JSON Schema for any command's input

MCP tools

search_models, get_model_pricing, estimate_cost, compare_models — all read-only. Each returns JSON with fetched_at. No write/refresh tool exists because data is always live.