MCP server

SLXD AI API Pricing Official

app.slxd/aiapipricing

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Look up, compare and track AI model API prices from an AI assistant. No sign-in needed.

Website

At a glance

Type

MCP server

Publisher

slxd.app (verified by the MCP Registry)

Status

Working at last check

Tools

10

Token cost

About 1,566 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http aiapipricing https://aiapipricing.slxd.app/mcp/aiapipricing

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.aiapipricing]
url = "https://aiapipricing.slxd.app/mcp/aiapipricing"

Gemini CLI

{"mcpServers":{"aiapipricing":{"httpUrl":"https://aiapipricing.slxd.app/mcp/aiapipricing"}}}

Cursor

{"mcpServers":{"aiapipricing":{"url":"https://aiapipricing.slxd.app/mcp/aiapipricing"}}}

VS Code

{"servers":{"aiapipricing":{"type":"http","url":"https://aiapipricing.slxd.app/mcp/aiapipricing"}}}

Antigravity

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

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"aiapipricing","server_url":"https://aiapipricing.slxd.app/mcp/aiapipricing","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"aiapipricing","server_url":"https://aiapipricing.slxd.app/mcp/aiapipricing"}

Tools

• compare_models ~164 tokens
  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)
• data_sources ~83 tokens
  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.
• find_tools ~162 tokens
  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.
• get_model_price ~307 tokens
  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 dimensio
• list_providers ~108 tokens
  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.
• price_history ~235 tokens
  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
• recent_changes ~92 tokens
  Lists recent price increases, decreases, additions and removals across the catalogue, newest first.
• run_tool ~187 tokens
  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.
• search_models ~131 tokens
  Searches the catalogue of AI models and returns their current prices, with a confidence level and the sources backing each price.
• tool_schema ~97 tokens
  Returns the full input schema of a single tool, including which arguments are required. Call it after find_tools and before run_tool.

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