Send a prompt to ChatGPT anonymously and get the answer with its web sources, as JSON.
A hosted Model Context Protocol (MCP) server that gives Claude, Cursor, Windsurf and any other MCP client one ChatGPT tool. Send a prompt anonymously and get the answer back as markdown together with the web pages ChatGPT consulted, as structured JSON, with no OpenAI account and no API key of your own.
1,000 free credits every month, no card required, which is 100 prompts.
https://mcp.hasdata.com/mcp?apis=chatgpt
An MCP client and a HasData API key from the dashboard, free to create with no card, and the free tier covers 100 calls a month at the 10-credit rate. This is a remote server, so the simplest path is a URL and an x-api-key header, with no container to run and no OpenAI billing anywhere in the flow. A client that only speaks stdio reaches it through a thin launcher, published as @hasdata/chatgpt-mcp on npm and hasdata-chatgpt-mcp on PyPI, shown below.
The server URL is the same for every client. We run it hands-on in Claude Code and Claude Desktop. The other blocks follow each client's own documented format for a remote server.
| Field | Value |
|---|---|
| URL | https://mcp.hasdata.com/mcp?apis=chatgpt |
| Transport | HTTP, streamable |
| Auth header | x-api-key: HASDATA_API_KEY |
Clients with OAuth support can add the same URL as a connector and sign in without putting a key in a config file.
claude mcp add --transport http chatgpt "https://mcp.hasdata.com/mcp?apis=chatgpt" \
--header "x-api-key: HASDATA_API_KEY"
{
"mcpServers": {
"chatgpt": {
"type": "http",
"url": "https://mcp.hasdata.com/mcp?apis=chatgpt",
"headers": { "x-api-key": "HASDATA_API_KEY" }
}
}
}
{
"mcpServers": {
"chatgpt": {
"type": "streamable-http",
"url": "https://mcp.hasdata.com/mcp?apis=chatgpt",
"headers": { "x-api-key": "HASDATA_API_KEY" }
}
}
}
{
"servers": {
"chatgpt": {
"type": "http",
"url": "https://mcp.hasdata.com/mcp?apis=chatgpt",
"headers": { "x-api-key": "HASDATA_API_KEY" }
}
}
}
Prompts, not code. Paste one in and the agent picks the tool itself. Each is annotated with the calls it takes, because every successful call costs 10 credits.
Ask ChatGPT what the current state of the Artemis program is, and list the sources it used.
One call, 10 credits. The answer and the sources come back together.
Ask ChatGPT the same question in German.
One call, 10 credits. The answer follows the language of the prompt, so write the prompt in the language you want back.
Ask ChatGPT what happened in AI this week, with Berlin as the current date.
One call, 10 credits. timezone is what fixes the meaning of "this week".
Put the same question to ChatGPT three times and show where the answers differ.
Three calls, 30 credits. Each request is a fresh conversation, so there is no carry-over between them.
| Tool | What it returns |
|---|---|
hasdata_chatgpt_chat_getChatgptAnswer | The answer as markdown, the web sources ChatGPT consulted with their domain and title, the conversation title it generated, the model that answered, and whether a web search was used. 10 credits a call |
One tool, 10 credits per successful call.
hasdata_chatgpt_chat_getChatgptAnswer
| Parameter | Type | Required | Notes |
|---|---|---|---|
prompt | string | yes | The question or instruction, up to 8000 characters |
timezone | string | IANA zone name such as Europe/Berlin. It sets what ChatGPT treats as today |
Everything lands under conversation. The answer is in answer as markdown, with title holding the name ChatGPT generated for the thread, model the model that answered, and usedWebSearch saying whether it went to the web at all. finishReason and complete tell a truncated answer from a finished one.
{
"conversation": {
"answer": "As of **October 5, 2026**, NASA's Artemis program has made substantial progress…",
"title": "Artemis developments cited",
"model": "gpt-5-6",
"usedWebSearch": true,
"finishReason": "stop",
"complete": true,
"sources": [
{ "title": "Artemis News - NASA", "url": "https://www.nasa.gov/artemis-news/", "domain": "www.nasa.gov" }
]
}
}
Your client almost never sees an HTTP error code from a tool call. The MCP layer answers 200 and puts the failure inside the result, with isError set to true and the reason as text.
sources is uneven, and partly absent. In a measured answer carrying twenty sources, every one had title, url and domain, eleven had publishedDate and only five had snippet. Read each field defensively rather than assuming the shape of the first element holds for the rest.
No web search means no sources. usedWebSearch is false when ChatGPT answers from the model alone, and sources is then empty or missing. A prompt about a stable fact often takes that path, so ask for current information when citations are the point.
Every call is a fresh conversation. There is no memory between requests, so a follow-up has to carry its own context in the prompt. conversationId identifies the thread that answered, not a thread you can continue.
A truncated answer still succeeds. Check complete and finishReason before treating answer as the whole response.
Each successful call spends credits from the connected account. A call that fails validation is not billed.
The ChatGPT tool costs 10 credits per successful call. Answer length does not change the price.
The free tier is 1,000 credits every month with no card, which is 100 prompts.
Paid plans start at $59 a month for 200,000 credits, which is 20,000 calls. The unit price falls on larger plans. Current numbers are on the plans page.
| OpenAI API | This server | |
|---|---|---|
| Account | Your own OpenAI account and billing | One HasData key |
| What you get | The model's answer | The answer plus the web sources behind it |
| Web search | A separate tool you wire up | Included, with usedWebSearch reporting whether it ran |
| Output | Your own schema | Parsed JSON with the sources already split out |
The two are not substitutes. The OpenAI API is the right call when you need system prompts, tools, streaming and conversation state. This server is the right call when you want what ChatGPT publicly answers, with its citations, and no account of your own.
No. The server answers anonymously through HasData, and the only credential involved is your HasData key.
Whichever ChatGPT serves anonymously at the time. The response reports it in model, so read it rather than assuming. A measured call returned gpt-5-6.
No. Each request is a fresh thread with no memory of earlier ones. Carry the context in the prompt instead.
The language of the prompt. Ask in German and the answer comes back in German, or ask explicitly for a language in the prompt.
No. HasData is an independent web data provider and is not affiliated with, endorsed by or sponsored by OpenAI. All trademarks belong to their owners.
The server reads what ChatGPT answers publicly to an anonymous visitor. It does not log in, and it does not reach private conversations or account data.
| Product page and request builder | ChatGPT Scraper API |
| Endpoint documentation | ChatGPT Scraper API docs |
| Server documentation | MCP server docs |
| Every tool in one server | HasData/hasdata-mcp |
| Client walkthroughs | MCP clients and integrations |
| Plans and credit costs | Plans and credit costs |
npm install
npm test
The tests in test/ assert the tool contract, the part that can break without a commit here. They check that ?apis=chatgpt returns the one expected tool, that its name and required parameter have not changed, that it carries a description, and that a real call still puts the answer under conversation.
The parameter table and the sample above were read from the live schema and from real calls rather than from documentation. A correction is welcome when a field or a failure mode has changed. Open an issue with the response you saw.
MIT
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
npx -y @hasdata/chatgpt-mcpMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"com-hasdata-chatgpt": {
"command": "npx",
"args": [
"-y",
"@hasdata/chatgpt-mcp"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup reference@hasdata/chatgpt-mcpnpmHasData ChatGPT works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.