inferenceindexer-mcp

AI inference pricing for agents: live and historical model prices, provider comparison.

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What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    AI inference pricing for agents: live and historical model prices, provider comparison.

    How to connect

    How to connect inferenceindexer-mcp to Claude

    The server address to paste into Claude settings:

    https://api.inferenceindexer.ai/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect inferenceindexer-mcp to ChatGPT

    The server address to paste into ChatGPT settings:

    https://api.inferenceindexer.ai/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect inferenceindexer-mcp to Cursor

    The server address to paste into Cursor settings:

    https://api.inferenceindexer.ai/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (10)

    Raw names from tools/list. Only developers need these.

    recommend_modelsRecommend 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). limit: Max recommendations (1-20, default 5). Returns: ranked recommendations with endpoint_config and ranking evidence.
    explain_modelGet 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.
    search_modelsSearch 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.
    get_modelGet 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_model_historyGet 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.
    list_providersList all inference providers with model counts and price stats.
    get_providerGet 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.
    get_composite_latestGet 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_composite_historyGet SIT-Composite index history / trend over time. Args: days: History window in days (1-90, default 30). Returns: historical composite index values.
    compare_providersCompare 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).