MCP Marketing Analytics
Official# MCP Marketing Analytics
A minimal MCP server for marketing analytics data discovery and querying, starting with a Google Ads integration layer.
## Features
- Data source discovery
- Google Ads account discovery
- Field discovery for metrics and dimensions
- Data query execution with mock fallback and real Google Ads support when configured
## Local setup
1. Install dependencies:
```bash
npm install
```
2. Copy the environment template:
```bash
cp .env.example .env
```
3. Build the project:
```bash
npm run build
```
4. Start the server:
```bash
npm start
```
## Testing with MCP Inspector
Run the inspector against the local server:
```bash
npx @modelcontextprotocol/inspector node dist/server.js
```
### Example tool calls
Health check:
```json
{
"name": "health_check",
"arguments": {}
}
```
Discover sources:
```json
{
"name": "data_source_discovery",
"arguments": {
"search": "google"
}
}
```
Discover accounts:
```json
{
"name": "accounts_discovery",
"arguments": {
"source": "AW"
}
}
```
Discover fields:
```json
{
"name": "field_discovery",
"arguments": {
"source": "AW",
"search": "cost"
}
}
```
Run a query:
```json
{
"name": "data_query",
"arguments": {
"source": "AW",
"accounts": ["1234567890"],
"fields": ["date", "campaign_name", "clicks", "cost"],
"dateRange": {
"start": "2026-07-01",
"end": "2026-07-07"
},
"filters": ["clicks > 100"]
}
}
```
Retrieve query result:
```json
{
"name": "get_query_results",
"arguments": {
"scheduleId": "schedule-123"
}
}
```
## Google Ads configuration
### Public multi-tenant connector
Production uses OAuth per user. The service keeps only its Google Ads developer
token and Google OAuth application credentials in Vercel; each user's Google
refresh token is encrypted and stored separately in Supabase. See
[`docs/multi-tenant-oauth.md`](docs/multi-tenant-oauth.md) for database migration,
redirect URI, environment configuration, and rollout instructions.
### Local single-user mode
To enable the real Google Ads API flow, define these environment variables in your `.env` file:
```bash
GOOGLE_ADS_DEVELOPER_TOKEN=
GOOGLE_ADS_CLIENT_ID=
GOOGLE_ADS_CLIENT_SECRET=
GOOGLE_ADS_REFRESH_TOKEN=
GOOGLE_ADS_CUSTOMER_ID=
GOOGLE_ADS_LOGIN_CUSTOMER_ID=
GOOGLE_ADS_API_VERSION=v25
GOOGLE_ADS_MOCK_MODE=false
```
### OAuth 2.0 setup for Google Ads
1. Create or select a Google Cloud project.
2. Enable the Google Ads API in the Google Cloud console.
3. Create OAuth 2.0 Client ID credentials for a desktop application.
4. Add the following OAuth scopes to the consent screen:
- `https://www.googleapis.com/auth/adwords`
5. Use a redirect URI such as:
- `http://localhost`
6. Complete the OAuth authorization flow and store the generated refresh token in `GOOGLE_ADS_REFRESH_TOKEN`.
7. Insert your Google Ads developer token and customer IDs in the environment variables above.
### Recommended values for the environment file
- `GOOGLE_ADS_DEVELOPER_TOKEN`: your Google Ads manager/developer token.
- `GOOGLE_ADS_CLIENT_ID`: OAuth client ID from Google Cloud.
- `GOOGLE_ADS_CLIENT_SECRET`: OAuth client secret from Google Cloud.
- `GOOGLE_ADS_REFRESH_TOKEN`: refresh token obtained after the OAuth flow.
- `GOOGLE_ADS_CUSTOMER_ID`: the Google Ads customer ID you want to query.
- `GOOGLE_ADS_LOGIN_CUSTOMER_ID`: the manager/customer ID used for login context, often the same as the customer ID.
- `GOOGLE_ADS_API_VERSION`: Google Ads API version; defaults to `v25`.
- `GOOGLE_ADS_MOCK_MODE`: opt-in demo data mode; keep `false` for the real integration.
### Local OAuth helper
A local helper is now included so you can complete the flow directly from this project.
1. Make sure your `.env` contains `GOOGLE_ADS_CLIENT_ID` and `GOOGLE_ADS_CLIENT_SECRET`.
2. Build the project:
```bash
npm run build
```
3. Start the OAuth helper:
```bash
npm run oauth:google-ads
```
4. Open the printed URL in your browser, approve the consent screen, and return to the terminal.
5. The helper will exchange the authorization code for tokens and print the response.
### Example OAuth flow
If you want to test the flow manually, use the standard OAuth 2.0 desktop-app flow:
```bash
https://accounts.google.com/o/oauth2/v2/auth?client_id=YOUR_CLIENT_ID&redirect_uri=http://localhost:3000/callback&response_type=code&access_type=offline&scope=https://www.googleapis.com/auth/adwords&prompt=consent
```
Then exchange the returned authorization code for a refresh token using the local helper above.
### Important notes
- The Google Ads API requires a valid developer token and OAuth credentials.
- The current implementation uses mock data whenever the required credentials are missing.
- Once the credentials are present, the server will attempt to call the real Google Ads API endpoints.
## Connection diagnostics
Use the `google_ads_connection_status` MCP tool to verify production configuration
without returning credential values. Missing credentials now produce a clear error;
mock responses are used only when `GOOGLE_ADS_MOCK_MODE=true`.
TDQS
Scored across 5 tools
Each tool targets a distinct step in the analytics workflow: source discovery, account discovery, field discovery, query execution, and result retrieval. There is no overlap between these purposes, so an agent can confidently select the right tool.
The first three tools follow a consistent 'X_discovery' pattern, but the last two deviate with 'data_query' and 'get_query_results', mixing structural conventions. While all names use snake_case, the inconsistency in pattern makes the naming less predictable.
With only five tools, the set is well-scoped for a focused marketing analytics server. Each tool serves a necessary function in the pipeline without redundancy or bloat.
The tool set covers the full discovery-to-results lifecycle: discover sources, accounts, fields, execute a query, and retrieve results. There are no obvious gaps for read-only analytics operations.