Use readygpu in your AI assistant

Ask Claude, ChatGPT or your coding assistant which graphics card or Mac runs a model, what it costs today in India, and how two cards compare. It answers from the same catalogue and prices as this site. Read-only, free, and no account or key.

Server URL

readygpu runs an MCP (Model Context Protocol) server. Give your assistant this address:

https://readygpu.com/api/mcp

Streamable HTTP · no sign-in · read-only · 6 tools

Set up your assistant

Pick yours. Where a config file already lists other servers, add the readygpu entry beside them.

Claude (claude.ai and Claude Desktop)

Works on Free, Pro, Max, Team and Enterprise plans. Free allows one custom connector. On Team and Enterprise, an owner adds it for the organisation first.

  1. Open Customize › Connectors.
  2. Click + Add, then Add custom connector.
  3. Name it readygpu, paste https://readygpu.com/api/mcp as the remote MCP server URL and click Continue.
  4. Review the detected settings and click Continue. Under Authentication, choose No sign in, then click Add.
  5. In a chat, click + at the lower left, open Connectors and switch readygpu on.

On Team and Enterprise plans an owner adds it under Organization settings › Connectors (Add, then Custom › Web). Members then find it under Customize › Connectors and click Connect.

Official guide: Claude Help Center: custom connectors

Claude Code

Run this in a terminal:

Terminal
claude mcp add --transport http readygpu https://readygpu.com/api/mcp

That adds it to the current project. Add --scope user to have it in every project. Check it with claude mcp list, or /mcp inside Claude Code.

Official guide: Claude Code docs: MCP

ChatGPT

OpenAI offers custom MCP servers on ChatGPT Business, Enterprise and Edu, on the web only (not the mobile apps). On Business only admins and owners can add one; on Enterprise and Edu, admins can allow other members.

  1. Go to chatgpt.com/plugins, click the + button and choose Add custom MCP server.
  2. Name it readygpu, enter https://readygpu.com/api/mcp as the Server URL and choose No authentication.
  3. Review the warning, tick I understand and want to continue, then click Create as a plugin.
  4. Open the new plugin in your plugins and click + to install it.
  5. In a new chat, type @ in the prompt box and pick readygpu.

Official guides: OpenAI: add a custom MCP server · OpenAI Help Center: plans and permissions

Cursor

Add this to ~/.cursor/mcp.json to have it in every project, or to .cursor/mcp.json in one project:

~/.cursor/mcp.json
{
  "mcpServers": {
    "readygpu": {
      "url": "https://readygpu.com/api/mcp"
    }
  }
}

Turn it on or off under Customize in the sidebar. Cursor asks before it runs each tool unless you allow it.

Official guide: Cursor docs: MCP

VS Code (GitHub Copilot)

Works on every Copilot plan, Free included. With Copilot Business or Enterprise, your organisation's MCP servers in Copilot policy must be on; it is off by default.

  1. Open the Command Palette and run MCP: Add Server.
  2. Choose HTTP, paste https://readygpu.com/api/mcp, and enter readygpu as the server ID.
  3. When asked where to save it, choose Copilot Global to have it in every workspace.
  4. In Copilot Chat, click Configure Tools to check readygpu's tools are on. If VS Code asks whether you trust the server, confirm.

Or add it to the file yourself:

~/.copilot/mcp-config.json
{
  "mcpServers": {
    "readygpu": {
      "type": "http",
      "url": "https://readygpu.com/api/mcp"
    }
  }
}

In .vscode/mcp.json, or the profile's mcp.json (MCP: Open User Configuration), the top-level key is servers instead of mcpServers.

Official guides: VS Code docs: MCP servers · GitHub docs: MCP in Copilot

Devin Desktop (formerly Windsurf)

Windsurf became Devin Desktop in June 2026. Its default agent, Devin Local, reads MCP servers from ~/.config/devin/mcp_config.json (%APPDATA%\devin\mcp_config.json on Windows):

~/.config/devin/mcp_config.json
{
  "mcpServers": {
    "readygpu": {
      "url": "https://readygpu.com/api/mcp",
      "transport": "http"
    }
  }
}

With Devin CLI installed, devin mcp add -s user readygpu https://readygpu.com/api/mcp adds it for you. Devin Local asks before each tool call; you can allow readygpu's tools for the session or for good. The older Cascade agent takes serverUrl in place of url.

Official guides: Devin docs: MCP configuration · Devin docs: Devin Local · Devin docs: Cascade MCP

Gemini CLI

Run this in a terminal:

Terminal
gemini mcp add --transport http --scope user readygpu https://readygpu.com/api/mcp

Without --scope user it goes in the current project's .gemini/settings.json. To edit the file yourself, use httpUrl: in Gemini CLI, url means an SSE server.

~/.gemini/settings.json
{
  "mcpServers": {
    "readygpu": {
      "httpUrl": "https://readygpu.com/api/mcp"
    }
  }
}

Check it with /mcp inside Gemini CLI.

Official guide: Gemini CLI docs: MCP servers

OpenAI Codex

Run this in a terminal:

Terminal
codex mcp add readygpu --url https://readygpu.com/api/mcp

Or add it to ~/.codex/config.toml:

~/.codex/config.toml
[mcp_servers.readygpu]
url = "https://readygpu.com/api/mcp"

The Codex CLI, the Codex IDE extension and the ChatGPT desktop app share this configuration. Check it with codex mcp list, or /mcp in the Codex terminal UI.

Official guide: OpenAI docs: Codex and MCP

Any other MCP client

  • Server URL: https://readygpu.com/api/mcp
  • Transport: Streamable HTTP (often labelled HTTP or streamable-http). There is no SSE stream and no session.
  • Authentication: none. No key, token or header.
  • Tools: 6, all read-only.

A client that can only start local (stdio) servers, or only speaks the older SSE transport, cannot connect to it directly.

What it can look up

The server has 6 tools, all read-only. Your assistant picks which to call; you just ask.

  • Search open models search_models Find open-weight AI models by name or task (chat, coding, agentic, vision, reasoning). Returns each model's slug, size, context length and licence; use the slug with hardware_for_model.
  • Find graphics cards or machines find_hardware List graphics cards or complete machines (Macs, mini PCs) priced in a market, with memory, bandwidth, today's best price and the estimated speed on a model. Filter by maximum price and minimum memory; sort by price, speed, value or price per GB.
  • Hardware details hardware_details One graphics card or machine in a market: its specifications, every current price (new and used), and which models it runs fully in memory at a context length, how fast.
  • Hardware to run a model hardware_for_model For one model: how much memory it needs at each context length, the cheapest, best-value and fastest hardware that runs it fully in memory in a market, and their prices and speeds.
  • Best hardware lists best_hardware The ranked 'best for local AI' lists of a market (all graphics cards, cards under a price, used cards, Macs and mini PCs): best first by the most capable model each runs fully in memory, with prices.
  • Compare two compare_hardware Two graphics cards or machines side by side in a market: memory, price, how many models each runs fully in memory, and the estimated speed of each on every model.

Things to ask

  • Which graphics card do I need to run Llama 3.3 70B at 32k context, and what does it cost in India?
  • What's the best graphics card under ₹1,00,000 for running AI models at home in India?
  • Compare the RTX 3090 and the RTX 5090 for running local models.
  • Which Macs run Qwen3 32B fully in memory, and how fast?

It prices in the US unless you say you are in the UK, Germany, India or Canada. Speeds are estimates from memory bandwidth, worked out as the methodology explains, and every answer links the page it came from.

For developers and agents

  • MCP server card: the server, its transport and its tools, as JSON.
  • Agent skill: when an agent should reach for readygpu, and how to use it.
  • llms.txt: the whole site described for language models.
  • Public API: the same data over REST, with its OpenAPI document at /api/docs-json.
  • Every page also answers Accept: text/markdown with a markdown version of itself.