Official Supermetrics skill. Query marketing data from 100+ platforms including Google Analytics, Meta Ads, Google Ads, and LinkedIn. Requires API key.
Scanned 9/5/2026
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---
name: supermetrics
description: "Official Supermetrics skill. Query marketing data from 100+ platforms including Google Analytics, Meta Ads, Google Ads, and LinkedIn. Requires API key."
---
# Supermetrics Marketing Data
Query marketing data from 100+ platforms including Google Analytics, Meta Ads, Google Ads, and LinkedIn.
## Usage
Import the helper module:
```python
from supermetrics import (
discover_sources,
discover_accounts,
discover_fields,
query_data,
get_results,
get_today,
search,
health,
)
```
## Functions
### discover_sources()
List all available marketing platforms.
```python
result = discover_sources()
for src in result['data']['sources']:
print(f"{src['id']}: {src['name']}")
```
### discover_accounts(ds_id)
Get connected accounts for a data source.
**Common data source IDs:**
| ID | Platform |
|----|----------|
| FA | Meta Ads (Facebook) |
| AW | Google Ads |
| GAWA | Google Analytics |
| GA4 | Google Analytics 4 |
| LI | LinkedIn Ads |
| AC | Microsoft Advertising (Bing) |
```python
result = discover_accounts("GAWA")
for acc in result['data']['accounts']:
print(f"{acc['account_id']}: {acc['account_name']}")
```
### discover_fields(ds_id, field_type=None)
Get available metrics and dimensions.
```python
# Get all fields
result = discover_fields("GAWA")
# Get only metrics
result = discover_fields("GAWA", "metric")
# Get only dimensions
result = discover_fields("GAWA", "dimension")
```
### query_data(...)
Execute a marketing data query. Returns schedule_id for async retrieval.
```python
result = query_data(
ds_id="GAWA",
ds_accounts="123456789",
fields=["date", "sessions", "pageviews", "users"],
date_range_type="last_7_days"
)
schedule_id = result['data']['schedule_id']
```
**Parameters:**
- `ds_id` (required): Data source ID
- `ds_accounts` (required): Account ID(s) from discover_accounts()
- `fields` (required): Field ID(s) from discover_fields()
- `date_range_type`: `last_7_days`, `last_30_days`, `last_3_months`, `custom`
- `start_date`, `end_date`: For custom date range (YYYY-MM-DD)
- `filters`: Filter expression (e.g., `"country == United States"`)
- `timezone`: IANA timezone (e.g., `"America/New_York"`)
**Filter operators:**
- `==`, `!=` - equals, not equals
- `>`, `>=`, `<`, `<=` - comparisons
- `=@`, `!@` - contains, does not contain
- `=~`, `!~` - regex match
### get_results(schedule_id)
Retrieve query results.
```python
result = get_results(schedule_id)
for row in result['data']['data']:
print(row)
```
### get_today()
Get current UTC date for date calculations.
```python
result = get_today()
print(result['data']['date']) # "2026-02-03"
```
### search(query)
Search across Supermetrics resources for guidance and suggestions.
```python
result = search("facebook ads metrics")
print(result['data'])
```
### health()
Check Supermetrics server health status.
```python
result = health()
print(result['data']['status']) # "healthy"
```
## Workflow Example
```python
from supermetrics import (
discover_accounts,
discover_fields,
query_data,
get_results,
)
# 1. Find accounts
accounts = discover_accounts("GAWA")
account_id = accounts['data']['accounts'][0]['account_id']
# 2. See available fields
fields = discover_fields("GAWA", "metric")
print([f['id'] for f in fields['data']['metrics'][:5]])
# 3. Query data
query = query_data(
ds_id="GAWA",
ds_accounts=account_id,
fields=["date", "sessions", "users", "pageviews"],
date_range_type="last_7_days"
)
# 4. Get results
data = get_results(query['data']['schedule_id'])
for row in data['data']['data']:
print(row)
```
## Response Format
All functions return:
```python
{"success": True, "data": {...}} # Success
{"success": False, "error": "..."} # Error
```
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