Read-only MCP server for the OpenAI Ads API: campaigns, ad groups, ads, and insights.
Openai MCP server exists for a simple reason — assistants are far more useful when they can act on Openai directly instead of describing what you should do. Read-only MCP server for the OpenAI Ads API: campaigns, ad groups, ads, and insights.
A Model Context Protocol (MCP) server for the OpenAI Ads (Advertiser) API. It lets MCP-compatible clients — Claude Desktop, Cursor, VS Code, and others — read your OpenAI Ads campaigns, ad groups, ads, and performance insights through natural language.
The OpenAI Ads API exposes an advertiser's account, campaigns, ad groups, ads, and reporting. This server wraps the read endpoints of that API as MCP tools so an AI assistant can answer questions like:
Once Openai is connected, these are the calls the assistant has available:
get_ad_account — Fetch the ad account for the configured key. Great as a connectivity checklist_campaigns — List campaigns (objective, budget, country targeting)get_campaign — Fetch a single campaign by IDlist_ad_groups — List ad groups, optionally filtered by campaignget_ad_group — Fetch a single ad group by ID (bidding config, context hints)list_ads — List ads, optionally filtered by ad groupget_ad — Fetch a single ad by ID (creative + review status)get_account_insights — Performance insights for the whole accountget_campaign_insights — Performance insights for one campaignget_ad_group_insights — Performance insights for one ad groupget_ad_insights — Performance insights for one adCursor — The Cursor tool exposed by this serverBeing a remote server, there is no local install. You register the endpoint with your client, authorise it once, and the tools appear.
You will need 2 environment variables: OPENAI_ADS_API_KEY, OPENAI_ADS_BASE_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Openai's toolset — get_ad_account, list_campaigns, get_campaign and 9 more — is a fair guide to whether it matches your workflow. It is maintained by HYPD-AI; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| get_ad_account | Fetch the ad account for the configured key. Great as a connectivity check. |
| list_campaigns | List campaigns (objective, budget, country targeting). |
| get_campaign | Fetch a single campaign by ID. |
| list_ad_groups | List ad groups, optionally filtered by campaign. |
| get_ad_group | Fetch a single ad group by ID (bidding config, context hints). |
| list_ads | List ads, optionally filtered by ad group. |
| get_ad | Fetch a single ad by ID (creative + review status). |
| get_account_insights | Performance insights for the whole account. |
| get_campaign_insights | Performance insights for one campaign. |
| get_ad_group_insights | Performance insights for one ad group. |
| get_ad_insights | Performance insights for one ad. |
| Cursor | The Cursor tool exposed by this server. |
{
"mcpServers": {
"openai-ads": {
"command": "npx",
"args": ["-y", "@hypd-ai/openai-ads-mcp"],
"env": {
"OPENAI_ADS_API_KEY": "your-openai-ads-api-key"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| OPENAI_ADS_API_KEY | Credential the server authenticates with. | Yes |
| OPENAI_ADS_BASE_URL | Endpoint or connection string the server talks to. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.