openai-ads-mcp

Trakkr tracks the full AI-visibility funnel, organic and paid. This is the open-source paid-side companion.

openai-ads-mcp is a typed Model Context Protocol server for OpenAI Ads, ChatGPT Ads, and OpenAI's Advertiser API. It lets Claude, Cursor, Codex, VS Code, and other MCP clients inspect Ads accounts, read performance insights, build paused campaigns, upload creatives, manage audiences, and send conversion events.

It ships in two runtimes with the same tool names, arguments, defaults, safety model, and vendored OpenAPI reference:

The goal is simple: make OpenAI Ads workable from an AI assistant without making spend easy to trigger by accident.

Install

Python with uvx:

uvx openai-ads-mcp

Python with pip:

python -m pip install openai-ads-mcp
openai-ads-mcp

Node with npx:

npx -y openai-ads-mcp

Node with npm:

npm install -g openai-ads-mcp
openai-ads-mcp

For local development from this monorepo:

cd services/openai-ads-mcp/python
python -m pip install -e .
python -m openai_ads_mcp

cd ../typescript
npm install
npm run build
node dist/index.js

Related MCP server: facebook-business-mcp

Configuration

Create an Ads API key in OpenAI Ads Manager, then pass it as an environment variable.

export OPENAI_ADS_API_KEY="..."

Recommended first connection:

export OPENAI_ADS_MCP_READONLY=1
uvx openai-ads-mcp

Or with Node:

export OPENAI_ADS_MCP_READONLY=1
npx -y openai-ads-mcp

Readonly mode hides every write tool. They are absent from tools/list and cannot be called. Once you have confirmed the account and inspected data, unset OPENAI_ADS_MCP_READONLY to enable writes.

Optional environment variables:

Discovery Metadata

This repo includes server.json for the official MCP Registry and downstream MCP directories. The canonical registry name is:

io.github.trakkr-aisearch/openai-ads-mcp

The Node package includes the matching mcpName, and the Python package README includes the matching mcp-name marker for PyPI ownership verification.

MCP client examples

Claude Code, Python runtime

claude mcp add openai-ads \
  -e OPENAI_ADS_API_KEY=your_ads_key_here \
  -e OPENAI_ADS_MCP_READONLY=1 \
  -- uvx openai-ads-mcp

Claude Code, Node runtime

claude mcp add openai-ads \
  -e OPENAI_ADS_API_KEY=your_ads_key_here \
  -e OPENAI_ADS_MCP_READONLY=1 \
  -- npx -y openai-ads-mcp

Cursor or Claude Desktop

{
  "mcpServers": {
    "openai-ads": {
      "command": "uvx",
      "args": ["openai-ads-mcp"],
      "env": {
        "OPENAI_ADS_API_KEY": "your_ads_key_here",
        "OPENAI_ADS_MCP_READONLY": "1"
      }
    }
  }
}

Use "command": "npx" and "args": ["-y", "openai-ads-mcp"] for the Node runtime.

Codex CLI

[mcp_servers.openai_ads]
command = "uvx"
args = ["openai-ads-mcp"]
env = { OPENAI_ADS_API_KEY = "your_ads_key_here", OPENAI_ADS_MCP_READONLY = "1" }

Docker

The repository includes a root Dockerfile for directories and scanners that build MCP servers directly from source:

docker build -t openai-ads-mcp .
docker run --rm -i -e OPENAI_ADS_MCP_READONLY=1 openai-ads-mcp

The container starts the stdio MCP transport by default so MCP registries can introspect tools, resources, and prompts. For local use, pass OPENAI_ADS_API_KEY and keep OPENAI_ADS_MCP_READONLY=1 for first connection.

Streamable HTTP

The Node runtime can also serve MCP over Streamable HTTP for hosted or team deployments:

export OPENAI_ADS_MCP_HTTP_TOKEN="choose_a_long_random_token"
npx -y openai-ads-mcp --http

Defaults:

• URL: http://127.0.0.1:8080/mcp locally, or https://your-host/mcp behind a proxy.

• Health check: GET /healthz.

• Remote mode forces OPENAI_ADS_MCP_READONLY=1 unless OPENAI_ADS_MCP_HTTP_ALLOW_WRITES=1 is set.

• OPENAI_ADS_MCP_HTTP_TOKEN protects the MCP endpoint with Authorization: Bearer <token>.

• Clients may send X-OpenAI-Ads-API-Key per request, or the server can use a server-side OPENAI_ADS_API_KEY.

Useful hosted env vars:

For public hosted endpoints, keep writes disabled by default and inject Ads API keys server-side through your own OAuth or credential vault. Do not put a shared Ads API key in browser-visible config.

Tool Surface

The Python and Node runtimes expose the same 27 tools.

High-use tools

Safety Model

This server can affect real ad spend, so the defaults are deliberately cautious.

1. Create tools default to paused. build_campaign creates every object paused.

2. Activations are separate tools: set_campaign_state, set_ad_group_state, and set_ad_state.

3. Budget-setting paths enforce OPENAI_ADS_BUDGET_CEILING_USD, default 100.

4. To exceed the ceiling, pass confirm_budget=True.

5. OPENAI_ADS_MCP_READONLY=1 hides every write tool entirely.

6. Conversion ingest validates at most 1000 events per call, timestamps no older than 7 days, and timestamps no more than 10 minutes in the future.

7. The server never logs API keys or conversion user data.

MCP annotations are set on every tool. Read tools use readOnlyHint. Write tools use readOnlyHint=false. Activation and budget-changing tools are marked destructive and open-world so hosts can prompt before running them.

Worked Example

First, connect safely:

export OPENAI_ADS_API_KEY="..."
export OPENAI_ADS_MCP_READONLY=1
uvx openai-ads-mcp

Ask your assistant:

Call get_account and list_campaigns. Confirm the Ads key works and show me what already exists.

Then restart without readonly mode and build a paused campaign:

Use draft_context_hints for "AI visibility monitoring software" aimed at growth teams with comparison intent.

Then call build_campaign with:
- name: "AI visibility category test"
- budget_usd: 50
- ad_group: name "Growth teams", billing_event "click", max_bid_usd 1.25, context_hints from the draft
- ads: two chat_card variants using my uploaded file_id

Do not activate anything.

Review the returned campaign, ad group, ads, budget, targeting, and review status. When you are ready to go live, activate each layer explicitly:

Call set_campaign_state with state="activate".
Call set_ad_group_state with state="activate".
Call set_ad_state for the approved ad with state="activate".

The Organic Half

Paid placements answer: where did you buy attention?

Trakkr answers: where does your brand show up organically across ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, Reddit, citations, rankings, competitors, sentiment, prompts, reports, and actions?

Track the organic side at trakkr.ai. Use the Trakkr generator at trakkr.ai/create when you want to turn AI-search gaps into content briefs.

This MCP also exposes one optional resource:

openai-ads://trakkr-visibility

It returns a short paste-ready briefing that connects buying ChatGPT ad placements with tracking organic ChatGPT visibility. It is never injected into tool results.

Development

Python:

cd services/openai-ads-mcp/python
python -m pytest -q
python -c "import openai_ads_mcp; print('ok')"

Node:

cd services/openai-ads-mcp/typescript
npm install
npm run build
npm test
OPENAI_ADS_MCP_READONLY=1 node dist/index.js

OpenAPI drift check:

cd services/openai-ads-mcp/typescript
npm run check:openapi

Release Status

This package is beta. Before the first public release, confirm that the PyPI and npm package names openai-ads-mcp are available. See RELEASING.md.

License

MIT, copyright Trakkr.