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MCP for Claude, Cursor and ChatGPT

October 2026

Connect your assistant

You can connect UGESI in two ways. Chat apps, Claude and ChatGPT in the browser, the desktop app or on a phone, use the UGESI server on the internet: you paste an address and your key. Programs on your computer can also run the server file themselves.

Both ways need an API key. Every credit pack includes API keys, so MCP works once you have bought any pack. Free sign-up credits alone do not include a key. Create one in My account, in the API keys section, and give each assistant its own key.

Chat: Claude and ChatGPT

Nothing to install. The server address is https://ugesi.com/api/mcp/. Before a job that spends credits, the chat asks for your approval unless you allow it permanently.

Claude: chat on claude.ai, desktop and phone

In Claude open Customize, then Connectors, choose + Add and Add custom connector. Name it UGESI and paste the server address. Choose No sign in, add the request header below with your key, then choose Add. In a chat, turn UGESI on in the tools menu. The Free plan allows one custom connector. On Team and Enterprise plans an owner adds it in the organization settings.

Server address

https://ugesi.com/api/mcp/

Request header

Authorization: Bearer ugsk_your_key

ChatGPT: chat

On chatgpt.com open Plugins, choose + and Add custom MCP server. Name it UGESI and paste the address below with your key in place of ugsk_your_key. Choose No authentication, confirm, choose Create as a plugin and install it. In a new chat type @ and pick UGESI. ChatGPT has no field for a key, so the key sits in the address: treat that address like a password and give ChatGPT its own key. Whether you can add servers depends on your plan and workspace settings.

Server address with your key

https://ugesi.com/api/mcp/ugsk_your_key/

Programs on your computer

These programs start the UGESI server file on your computer. Besides the key you need:

  1. Node.js 18 or newer, free from nodejs.org. node --version shows what you have.
  2. The server file: Download ugesi-mcp.mjs (10 KB)

In the examples, replace /path/to/ugesi-mcp.mjs with where you saved the file (on Windows, for example C:/Users/you/Downloads/ugesi-mcp.mjs, with forward slashes) and ugsk_your_key with your key.

Claude Desktop

Open Settings, then Developer, then Edit Config. Paste this into claude_desktop_config.json, save and restart Claude. The UGESI tools appear in the tool list of a new chat.

claude_desktop_config.json

{
  "mcpServers": {
    "ugesi": {
      "command": "node",
      "args": ["/path/to/ugesi-mcp.mjs"],
      "env": { "UGESI_API_KEY": "ugsk_your_key" }
    }
  }
}

Claude Code

Run this once in a terminal. claude mcp list confirms that the server is connected.

claude mcp add --transport stdio --env UGESI_API_KEY=ugsk_your_key ugesi -- node /path/to/ugesi-mcp.mjs

Gemini CLI

Add the same block to settings.json in the .gemini folder of your user folder. Start gemini and type /mcp to see the UGESI tools.

~/.gemini/settings.json

{
  "mcpServers": {
    "ugesi": {
      "command": "node",
      "args": ["/path/to/ugesi-mcp.mjs"],
      "env": { "UGESI_API_KEY": "ugsk_your_key" }
    }
  }
}

ChatGPT: Codex

Codex, the OpenAI agent you sign in to with your ChatGPT account, runs local MCP servers. Add this to config.toml in the .codex folder. The command line and the editor extension share this file.

~/.codex/config.toml

[mcp_servers.ugesi]
command = "node"
args = ["/path/to/ugesi-mcp.mjs"]
env = { "UGESI_API_KEY" = "ugsk_your_key" }

ChatGPT: custom GPT

In the GPT editor open Configure, then Create new action, and import the schema from the address below. Under Authentication choose API Key, type Bearer, and paste your key. The GPT gets the same five operations.

https://ugesi.com/api/openapi/

Cursor

Add the same block to mcp.json in the .cursor folder of your user folder and reload Cursor.

~/.cursor/mcp.json

{
  "mcpServers": {
    "ugesi": {
      "command": "node",
      "args": ["/path/to/ugesi-mcp.mjs"],
      "env": { "UGESI_API_KEY": "ugsk_your_key" }
    }
  }
}

Check that it works

Ask the assistant: “List the UGESI video models and their rates.” It should call ugesi_list_models. Before the first paid job, ask it for an estimate.

Where it does not work yet

The Gemini app: we have not found a way to add your own MCP server there yet. Use Gemini CLI as shown above.

DeepSeek: the DeepSeek app and website do not connect to MCP servers. If you use DeepSeek models in a program that runs MCP servers, for example Claude Code connected to the DeepSeek API, add UGESI there as shown above.

The key is stored in a config file on your computer, in the connector settings in Claude or in the address in ChatGPT. Give each assistant its own key: its usage shows separately in My account, and you can revoke it at any time without touching the others.

Generate without leaving the assistant

Ask Claude for a product shot on marble. It calls UGESI, waits for the job and hands back the file. No tab switching, no copying prompts.

Five tools

List models with rates. Estimate a job before running it. Start a generation. Check a job. Compose a recipe from guided mode, the same vocabulary the site uses.

Estimate before you generate

Ask the assistant what a job costs and it calls the estimate tool. Credits, a dollar figure and whether the model is available. Nothing is held and no balance is needed, so planning a batch costs nothing.

Billing

Every call draws from the same credit balance as the browser. Failed jobs refund themselves. Paused or retired models return a clear error with alternatives.

Who can use it

Anyone with a credit pack bought in the last 12 months. Agents generate in loops, so every key gets a rate limit, a usage view and a way to revoke it at once.

What an assistant can and cannot do here

It can list models with current rates, start a generation, check a job and read a recipe. It cannot spend beyond your balance, change your account or access anything outside the five tools. The key you issue defines the limit.

Why this is not just an API wrapper

An assistant that can only generate has to guess which model to use. These tools expose rates and limits first, so the assistant can reason about cost before spending your credits. That changes the quality of its decisions.

What it costs to run

The same rates as the interface. An assistant spending your credits is still your balance. Every job appears in your history with the model, the prompt and the cost.

Where it is genuinely useful

Batch work with judgment in it. Twenty product shots, each on a different background. Or a set of variants where the assistant checks the result and reruns the ones that missed. That is work a form cannot do and a script does badly.

Keeping an assistant inside a budget

Give the assistant its own key. Its usage shows separately in your account, and revoking it stops the assistant without touching other integrations. Runs draw from the account balance, so the balance is the upper limit.

What to ask for

Specific jobs work better than open ones. Ask for six product shots on different backgrounds and it will plan the runs. Ask it to make something nice and it will spend your credits finding out what that means.

Reading the history afterwards

Every job an assistant runs appears in your history with the model, the prompt and the cost. Exactly like a job you started yourself. There is no separate log to reconcile and nothing hidden behind an agent.

What to do when a tool call fails

The five tools return the same errors as the API, in plain language the assistant can act on. Not enough credits names the amount. A paused model names replacements. An assistant that reads the error can usually fix the request itself.

The best AI models and tools, without another subscription

Pay only for what you generate. New accounts start with free credits, no card needed.

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