OpenNodes

Pre-price an invocation chain BEFORE spending money. Each step is either a concrete offering ("node_id/offering_id") or a `select` query that picks the best match, plus expected input and output tokens. Returns per-step cost bounds in USD, the pinned card_revision that makes each estimate enforceable at invocation, and chain totals. Use it to compare routes or budget a multi-model pipeline; nothing is invoked or charged.

Where AI models are served, by country: every known serving site (provider, region, city or facility, live or planned) with its evidence basis (claimed, documented, measured, attested), its source page, a map point (`geo`: lat, lon, precision; `derived` when only the region is known), and the models it serves. Sites whose provider publishes no model list are included with a note. Built from node cards, imported catalogs and curated location seeds. Use it to answer "which providers serve which models in Canada" or "what serves gpt-oss within 500 km of Montréal", or to check a residency requirement before choosing an offering; then search_offerings with `region` to pick one.

What each AI provider officially promises about where prompts, outputs and stored data stay: per provider (cloud, lab API, inference host or router), its commitments, each with a commitment level (processing: inference and stored data stay in the scope; storage: data at rest only; none; unstated), the region codes it covers, who gets it (default, opt_in, enterprise), the programme name, a short statement and the source page with the date it was checked. Includes routers and providers with no known sites. Use it to answer "which providers keep data in the EU by default" before choosing an offering; then find_locations or search_offerings with `region`.

Who runs a node and how it has behaved: operator, country and regions, endpoints, declared hardware, trust tier and its history (verifications, suspensions, reinstatements, with reasons), recent registry probe results with an availability summary, and its offerings with context window and price. Use it to vet a provider before relying on it; take node_id from search_offerings, recommend or get_offering results. For one offering's full card, use get_offering.

Full detail for one offering: endpoints, pricing, serving capabilities (context window, supported features, languages, hardware), data policy, trust tier, and the registry's observed probe results. Take node_id and offering_id from search_offerings or recommend results.

Recommend the best AI node + model for a task, with an enforceable cost estimate and human-readable reasons. Use this first when you know the task but not the model. Pass `task` (sent to this registry, which extracts features and discards the text) or `features` already extracted on your side with extractFeatures from @opennodes/core, which keeps the prompt private. Returns ranked candidates with score components, a cost estimate pinned to the node's card revision, an optional cheaper two-step scenario, and MCP tool categories the task likely needs. To browse instead, use search_offerings; to price a specific chain, use estimate.

Search AI inference offerings in the OpenNodes registry — registered nodes AND imported catalogs (OpenRouter, Hugging Face Inference Providers, models.dev, local nodes). All filters are optional and combine with AND. Returns { offerings, total, counts }: each offering has node_id, offering_id, model, pricing (USD per MTok), trust tier, serving capabilities, measured probe results, and a rank explanation. Use get_offering for one offering's full card, recommend to let the advisor choose.