"Understanding Inference Models" matching MCP tools:

• get_available_modelsA

  Gonka Second Opinion (multi-model)A

  List all AI models available on Gonka Network with live pricing. Models work as drop-in replacements for OpenAI and Anthropic — same SDK, same API calls. Use this when user asks which model to use or wants alternatives to GPT-4o / Claude. Returns: model IDs (use directly in openai.chat.completions.create), status, USD per 1M tokens. After this: call calculate_savings() to see annual savings with these models.

  ConnectorNo auth

• compare-llm-modelsA

  OptimTokenA

  Browse and filter the whole LLM catalogue and get back a ranked table: price, quality (ELO), efficiency and capabilities. Use this when the user wants to SEE THE FIELD — 'show me models under $1/1M', 'which providers have vision models', 'list open-weight models above ELO 1300'. For a single PICK under a budget use recommend-llm-model; to weigh 2-4 NAMED models against each other use compare-models-side-by-side. Prices come from optimtoken.optimnow.io where reachable; the response's `provenance` says which tier served them and whether they are vendor-verified. Filter by provider, price tier (category), openness, capability, price range, or minimum ELO score. Optionally enrich with business metrics for a use case. Price tier and openness are independent: a model can be Frontier-priced and open-weight at once. Reports both list-price cost and the optimized cost achievable with prompt caching and the batch API. IMPORTANT: Report all prices, costs, and scores EXACTLY as returned. Do NOT add commentary, opinions, or recommendations beyond what the data shows. Present the results as a table and let the user draw conclusions.

  ConnectorNo auth

• compare-models-side-by-sideA

  OptimTokenA

  Compare 2-4 named LLM models against all 8 use-case profiles at a chosen monthly volume, showing list and optimized cost for each. Use when the user names specific models to weigh against each other, rather than filtering the whole catalogue. If they also supply their own token counts, or a volume outside 10k/100k/1m, use estimate-llm-cost instead. Every name is resolved against the catalogue and the result is reported: a name that matched nothing, matched several models, or duplicated an earlier pick is stated explicitly. IMPORTANT: Report all prices and costs EXACTLY as returned, and repeat any name-resolution warning to the user — a missing column is not the same as a model that costs nothing.

  ConnectorNo auth

• enrich_providerA

  apis-ioB

  One call, pick your field groups — resolves a slug OR any identifier and returns exactly the groups you ask for, instead of chaining get_provider + get_provider_rating + get_provider_artifacts + get_provider_onboarding. Groups: profile, onboarding, artifacts, rating, insights. Understanding plan — the base groups moved with the rest of the discovery layer on 2026-08-31. Priced B2 (cross-catalog synthesis) — $0.05 per call under pay-as-you-go; included in Understanding and Influence. See apis://prices.

  ConnectorNo auth

• free2aitools_compareA

  Free2AIToolsA

  Compare 2-25 AI catalog entities side-by-side — any catalog entity type (models, datasets, papers, tools), not models only — showing FNI scores, factor breakdown (Semantic, Authority, Popularity, Recency, Quality), specs (params, VRAM, context length) where applicable, and license. USE WHEN you already have 2+ specific entity ids and want a structured side-by-side. DO NOT USE to discover entities, to run/execute a model, or to get a recommendation; the tool presents comparison facts for the caller to decide on, is not an inference router, and returns no paid placement. Read-only, no side effects, no billing. Cold upper-range multi-paper requests may return a transient 503 (retry after the indicated delay). Use free2aitools_select_model or free2aitools_search to discover candidates first, then compare the top ones.

  ConnectorNo auth

• list_endpointsA

  trading-mcpA

  List the full AI Rook endpoint catalog with prices (52 endpoints: trading intelligence, AI inference via local 456B MoE, blockchain data, dev tools, escrow). START HERE before calling any paid endpoint. Free.

  ConnectorNo auth

• ai_token_arbitrageA

  TrueCalciA

  Calculate multi-provider LLM API inference token costs, prompt caching economics (up to 95% discount), batch API savings (50%), and cross-model cost disparity multipliers across frontier and high-efficiency models (Anthropic Claude, OpenAI GPT, Google Gemini, DeepSeek). Behavior: Deterministic, idempotent calculation with zero external side effects. Models official public provider pricing cards per million input/output tokens. Incorporates prompt cache hit pricing reductions and asynchronous batch API discounts. Evaluates real-time pack age and freshness status (FRESH < 14 days, AGING 14-30 days, STALE > 30 days). Returns comprehensive model cost matrix, cheapest and most expensive model arbitrage analysis, cache savings, and monthly cost projections. Usage Guidelines: Use when budgeting AI agent inference costs, evaluating LLM providers, or deciding whether to implement prompt caching or batch inference. Do not use for cloud network egress; use cloud_egress_finops instead.

  ConnectorNo auth

• set_workspace_modelsA

  ZeroRank - Track and improve your AI search visibilityA

  Enable or disable AI models for a workspace. `models` is a partial map of model key -> boolean: unlisted models keep their current setting (pass replace: true to treat it as the complete map, disabling everything unlisted). Requires an owner or admin role. At least one available model must stay enabled. Models reported as available: false cannot be enabled (the surface is not delivering) — they may only be set false. Each enabled model spends answer-run budget per run according to its weight (see get_workspace_models).

  ConnectorOAuth

• model_profilesA

  PlanExeA

  Optional helper before plan_create. Returns model_profile options with plain-language guidance and currently available models in each profile. If no models are available, returns error code MODEL_PROFILES_UNAVAILABLE.

  ConnectorNo auth

• get_mission_statsA

  mcp-serverA

  Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.

  ConnectorNo auth

• billing.statusA

  Admin SubstituteA

  Check subscription status, plan details, billing cycle, and feature access. Useful for understanding what the business can and cannot do on their current plan.

  ConnectorNo auth

• cheapest_modelsA

  mcpA

  Find the cheapest current models, ranked by input price, output price, or a blended cost. The generic ranking covers generative text models (embeddings, OCR and realtime models are excluded — they price different work); pass category to rank a specific pool instead, e.g. 'embedding'. Use to answer 'what is the cheapest model for <use case>'.

  ConnectorNo auth

• list_modelsA

  UwearA

  List available AI generation models (image, video, edit, upscale engines) by type, with credit costs, capability limits, and model-specific production guidance. These are the AI models that render photoshoots — not the human models/avatars; for those, use list_avatars.

  ConnectorNo auth

• list_modelsA

  valemA

  List the ids of all currently registered Valem models (alphabetical).

  ConnectorNo auth

• check_image_serviceA

  Brainiall ImageA

  Check health status of Image API services and loaded models. Returns: dict with keys: - status (str): 'healthy' or error state - models (dict): Loaded model status per capability - version (str): API version

  ConnectorNo auth

• check_nlp_serviceA

  Brainiall NLPA

  Check health status of NLP API services and loaded models. Returns: dict with keys: - status (str): 'healthy' or error state - models (dict): Loaded model status per capability - version (str): API version

  ConnectorNo auth

• search_modelsA

  inferenceindexer-mcpA

  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 | zdr | eu (optional). limit: Max results (1-100, default 25). sort: Sort key, e.g. 'blended' (price), 'sit' (SIT score) (optional). Returns: models with input/output/blended $/M pricing, provider, tier.

  ConnectorNo auth

• kirk_billing_usageA

  Kirk — Unsupervised Structural Change DetectionA

  Return the caller's inference consumption over the last N days from the append-only Gate 2 events table. Purpose: Historical usage summary + per-tool breakdown for the caller's account. Use when: You need a usage report for the caller or an admin, or you are reconciling ledger debits against actual inference events. Do not use when: You need real-time cost — the `_cost` envelope on every agent-driven tool result covers that inline. Capability class(es): Meta (metering). Path fit: MCP only. Cost: 0 IU.

  ConnectorNo auth

• get_company_insightA

  apis-ioB

  UNDERSTANDING — Full demand-side profile for one company: 40-dimension readiness scores, adopted stack, and per-quarter history. Priced B2 (cross-catalog synthesis) — $0.05 per call under pay-as-you-go; included in Understanding and Influence. See apis://prices.

  ConnectorNo auth

• chatA

  mcpA

  Send a single prompt to any UnoRouter model and return the reply. Use search_models to find model IDs; :free models cost nothing (light per-model rate limit, rotate models if you hit 429).

  ConnectorNo auth

• suggest_flowA

  CNAPS.ai MCP ServerA

  RECOMMENDED FIRST STEP for any image/video/text processing request. Ask it which model or models to use — it answers for a single step and a multi-step chain alike, since a one-model flow is just a flow. Understands natural language (English, Korean, and more) and returns models in order, with parameter recommendations and wiring. Use this BEFORE list_models — it handles parameter inference (e.g. '4K' → scale_factor=4) and model selection automatically. Pass the result straight to create_flow.

  ConnectorOAuth