AI API Pricing

endpoint

https://aiapipricing.slxd.app/mcp/aiapipricing

protocol

streamable-http ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing · is it yours? claim it

karma

0 · newcomer

Is AI API Pricing live?

Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.

Is AI API Pricing free to use?

Yes — the hub reached it with no key and no payment.

What tools does AI API Pricing have?

10 tools: tool_schema, search_models, get_model_price, compare_models, price_history, find_tools, run_tool, recent_changes, ….

Is AI API Pricing safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• recent_changes open 1h ago

  Lists recent price increases, decreases, additions and removals across the catalogue, newest first.

  mcp-tool

  1234567891011121314151617

  {
    "type": "object",
    "properties": {
      "days": {
        "type": "integer",
        "default": 30,
        "maximum": 365,
        "minimum": 1
      },
      "limit": {
        "type": "integer",
        "default": 50,
        "maximum": 200,
        "minimum": 1
      }
    }
  }

  arguments 17 lines copy
• data_sources open 1h ago

  Explains where the prices come from: which sources are consulted, their weight and licence, when each last succeeded, and whether any is currently failing. Use this to judge how much to trust a price.

  mcp-tool

  1234

  {
    "type": "object",
    "properties": {}
  }

  arguments 4 lines copy
• list_providers open 1h ago

  Lists every provider in the catalogue and how many models each has. These are the houses that MAKE the models: a reseller (Vertex, Bedrock, Azure, OpenRouter, a subscription plan) is a sales channel, not a provider — ask `get_model_price` with a `channel` for what one of those charges.

  mcp-tool

  1234

  {
    "type": "object",
    "properties": {}
  }

  arguments 4 lines copy
• tool_schema unknown never probed

  Returns the full input schema of a single tool, including which arguments are required. Call it after find_tools and before run_tool.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "name"
    ],
    "properties": {
      "name": {
        "type": "string",
        "minLength": 1,
        "description": "Exact tool name, as returned by find_tools."
      }
    }
  }

  arguments 13 lines copy
• search_models unknown never probed

  Searches the catalogue of AI models and returns their current prices, with a confidence level and the sources backing each price.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "limit": {
        "type": "integer",
        "default": 20,
        "maximum": 100,
        "minimum": 1
      },
      "query": {
        "type": "string",
        "description": "Free text matched against name and id."
      },
      "provider": {
        "type": "string",
        "description": "Restrict to one provider slug, e.g. `openai`."
      }
    }
  }

  arguments 19 lines copy
• get_model_price unknown never probed

  Returns every current price for one model — input, output, cached reads, batch and priority tiers, context brackets — with the confidence level and which sources agree. By default these are the maker's own prices; pass `channel` to get what a reseller charges for the same model instead. Two dimensions can share a label, so the ones that would collide carry their qualifiers, e.g. 'Web search (context size: high)'.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "model"
    ],
    "properties": {
      "model": {
        "type": "string",
        "description": "Model id as `provider/slug`, e.g. `anthropic/claude-sonnet-4-5`."
      },
      "channel": {
        "enum": [
          "direct",
          "vertex",
          "bedrock",
          "azure",
          "sagemaker",
          "databricks",
          "snowflake",
          "watsonx",
          "cloudflare",
          "fireworks",
          "alibaba",
          "openrouter",
          "github_copilot",
          "coding_plan",
          "token_plan",
          "other"
        ],
        "type": "string",
        "description": "Sales channel to price. Omit for the maker's own price. `direct` is the maker, the rest resell the same model at their own rate; a channel that does not sell this model returns the model with no prices."
      }
    }
  }

  arguments 34 lines copy
• compare_models unknown never probed

  Returns the current prices of several models side by side. Amounts in credits are never converted to money, so a credit-billed model is not comparable to a token-billed one. Two dimensions can share a label, so the ones that would collide carry their qualifiers, e.g. 'Web search (context size: high)'.

  mcp-tool

  1234567891011121314151617

  {
    "type": "object",
    "required": [
      "models"
    ],
    "properties": {
      "models": {
        "type": "array",
        "items": {
          "type": "string",
          "description": "Model id as `provider/slug`, e.g. `anthropic/claude-sonnet-4-5`."
        },
        "maxItems": 8,
        "minItems": 2
      }
    }
  }

  arguments 17 lines copy
• price_history unknown never probed

  Returns a model's price over time. Each point is [date, amount] with the date as YYYY-MM-DD. The series holds only the points where the price CHANGED — prices are step functions, so a stable model is one point, not one per day; when a price changed twice on one day, both points are returned with the same date, in order. One series per price dimension: two dimensions can share a label, so the ones that would collide carry their qualifiers, e.g. 'Web search (context size: high)'.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "model"
    ],
    "properties": {
      "to": {
        "type": "string",
        "description": "ISO date, inclusive."
      },
      "from": {
        "type": "string",
        "description": "ISO date, inclusive."
      },
      "model": {
        "type": "string",
        "description": "Model id as `provider/slug`, e.g. `anthropic/claude-sonnet-4-5`."
      }
    }
  }

  arguments 20 lines copy
• find_tools unknown never probed

  Searches the full catalogue of available tools by keyword and returns the matching tool names with a short description. Use it when no directly-listed tool fits the task — many tools are available but not listed. Then call tool_schema for the one you picked, and run_tool to execute it.

  mcp-tool

  12345678910111213

  {
    "type": "object",
    "required": [
      "query"
    ],
    "properties": {
      "query": {
        "type": "string",
        "minLength": 1,
        "description": "Space-separated keywords, e.g. 'invoice pdf export'. Matched against tool names and descriptions; any term may match."
      }
    }
  }

  arguments 13 lines copy
• run_tool unknown never probed

  Executes a tool by name with the given arguments. Use it for tools that are not directly listed — look them up with find_tools and check their arguments with tool_schema first. Prefer a directly-listed tool whenever one fits. If the action is destructive, ask the user to confirm before calling it.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "name"
    ],
    "properties": {
      "name": {
        "type": "string",
        "minLength": 1,
        "description": "Exact tool name, as returned by find_tools."
      },
      "arguments": {
        "type": "object",
        "description": "Arguments object matching the tool's schema.",
        "propertyNames": {
          "type": "string"
        },
        "additionalProperties": {}
      }
    }
  }

  arguments 21 lines copy

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