io.github.DesMartin01/inferenceindexer-mcp

Compare the price of one model across the providers that host it. Args: model_id: Canonical model id, e.g. 'meta/muse-spark-1.1'. Returns: per-provider endpoints with pricing, showing where direct provider prices diverge (e.g. from OpenRouter's negotiated rate).

Get everything about one model in a single call: the full picture. Returns current pricing (input/output/blended, Cost/IQ, 24h/7d changes), a price-history summary with trend, all provider endpoints, the cheapest hand-verified endpoint with its native model id (for hot-swapping), privacy flags (ZDR/EU availability), and the AA intelligence score. Everything is as-of stamped. Args: model_id: Canonical model id, e.g. 'anthropic/claude-sonnet-5'. history_days: Price-history window (default 30, max 365). Returns: complete model profile with pricing, endpoints, privacy, quality.

Get SIT-Composite index history / trend over time. Args: days: History window in days (1-90, default 30). Returns: historical composite index values.

Get the current SIT-Composite index value + per-tier breakdown. The SIT-Composite is a usage-weighted mean of the top-50 models by token volume, reflecting what developers actually pay for inference.

Get full detail + current pricing for one model by its id. Args: model_id: Canonical model id, e.g. 'openai/gpt-5.6' or 'anthropic/claude-sonnet-5'. Returns: pricing, tier, SIT score, quality-adjusted price (Cost/IQ).

Get HISTORICAL price data / trends for one model. This is InferenceIndexer's differentiator: aggregators like OpenRouter expose only current price; this returns the price over time (input, output, blended $/M), enabling trend analysis. Args: model_id: Canonical model id, e.g. 'openai/gpt-5.6'. days: History window in days (1-365, default 30; plan-dependent). Returns: historical price series for the model.

Get detail for one provider: models, tier breakdown, price range. Args: provider_name: Provider name, e.g. 'DeepInfra', 'Novita', 'Venice'. Returns: provider detail with model list and pricing.

List all inference providers with model counts and price stats.

Recommend the best-value AI models for given constraints, ranked with receipts. The core answer endpoint: give it constraints and it returns the top models ranked by Cost/IQ (quality-adjusted price, lower is better), each with a plain-English 'why', a hot-swap endpoint_config (provider base_url + native model id, ready to call), as-of timestamps, and runner-ups. Args: budget_max_usd_per_m: Max blended price $/M (optional). context_min: Minimum context window in tokens (optional). modality: 'text' (default), 'vision', or 'any'. zdr: Require zero-data-retention providers (optional). eu_sovereign: Require EU-sovereign providers (optional). reasoning: Filter reasoning models (null = any, true/false). aa_min: Hard floor on the AA Intelligence Index score (quality gate). use_case: Task profile: support | volume | extraction | summarization | coding | research. prefer_callable: Demote models without a verified call recipe below callable ones. limit: Max recommendations (1-20, default 5). Returns: ranked recommendations with endpoint_config and ranking evidence.

Search and list AI inference models with current pricing. Args: query: Text search on model id/name (optional). tier: Filter by tier: frontier | standard | budget | micro (optional). limit: Max results (1-100, default 25). sort: Sort key: blended | input | output | sit_score | sit_adjusted_price (default sit_adjusted_price). Returns: models with input/output/blended $/M pricing, provider, tier.