Available Tools
Reference for all tools provided by the Aurora MCP server.
What Can You Do?
Aurora's MCP server gives your AI assistant access to your GEO tracking data. Here's what you can ask:
- Track your brand — Check how often AI platforms mention and cite your brand over time
- Spy on competitors — See which competing brands and domains appear in AI responses for your queries
- Analyze sources — Find out which URLs and domains AI models cite most frequently
- Spot trends — Compare visibility across providers, queries, and time periods
For complete workflow examples, see Use Cases.
Response Format
All data tools return a structured response with three sections:
{
"metadata": {
"campaign_id": "abc-123",
"period": { "from": "2025-01-01T...", "to": "2025-03-20T..." },
"total_rows": 847,
"rows_returned": 100,
"offset": 0,
"truncated": true
},
"summary": { },
"data": [ ]
}| Section | Description |
|---|---|
metadata | Time period, total row count, pagination info |
summary | Pre-aggregated data (by brand, by provider, etc.) — useful for quick answers without scanning all rows |
data | The actual data rows (paginated, default 100 per request) |
Pagination
Results are paginated with a default limit of 100 rows. Use limit and offset to page through large datasets:
- First request:
limit: 100, offset: 0(default) - Next page:
limit: 100, offset: 100 - Check
metadata.truncated— iftrue, there are more rows available
list_campaigns
List all GEO tracking campaigns for your account.
Parameters: None
Returns: Array of campaigns with:
| Field | Type | Description |
|---|---|---|
id | string | Campaign ID (use in other tools) |
name | string | Campaign name |
country | string | Target country |
country_code | string | ISO country code |
created_at | string | Creation timestamp |
Try asking:
- "List my Aurora campaigns"
- "Which campaigns do I have set up?"
- "Show me all my tracking campaigns"
Example response:
You have 2 campaigns:
- My Brand US — United States, created Jan 15, 2025
- My Brand DE — Germany, created Feb 3, 2025
get_brand_visibility
Get brand visibility scores across AI providers.
Parameters:
| Param | Type | Required | Description |
|---|---|---|---|
campaign_id | string | Yes | Campaign ID from list_campaigns |
start_date | string | No | Start date (YYYY-MM-DD) |
end_date | string | No | End date (YYYY-MM-DD) |
limit | number | No | Max rows to return (default 100) |
offset | number | No | Skip this many rows for pagination (default 0) |
Response includes:
Metadata: period, total_rows, rows_returned, truncated, unique_brands, unique_providers, unique_queries
Summary:
| Field | Description |
|---|---|
by_brand | Each brand with avg_visibility_score, total_mentions, total_citations, is_own_brand |
by_provider | Each provider with avg_visibility_score |
Data rows:
| Field | Type | Description |
|---|---|---|
date | string | Timestamp |
provider | string | AI provider (chatgpt, gemini, perplexity, copilot, google_ai_mode, ai_overview, yandex) |
query_text | string | The tracked query |
brand_name | string | Brand name |
brand_domain | string | Brand domain |
is_own_brand | boolean | Whether this is your own brand |
mentions | number | Number of mentions |
citations | number | Number of citations |
visibility_score | number | Visibility score (0–1) |
Try asking:
- "How visible is my brand across AI platforms this week?"
- "Show brand visibility trends for the last 30 days"
- "Compare my brand's mentions on ChatGPT vs Gemini"
Example response:
Here's your brand visibility for the past 7 days:
Provider Avg Score Mentions Citations ChatGPT 0.72 45 18 Gemini 0.58 31 12 Perplexity 0.85 52 34 Perplexity gives you the most visibility, with 0.85 avg score and the highest citation count. ChatGPT mentions you frequently but links to your site less often.
get_citations
Get citation data showing which URLs are cited by AI providers.
Parameters:
| Param | Type | Required | Description |
|---|---|---|---|
campaign_id | string | Yes | Campaign ID from list_campaigns |
start_date | string | No | Start date (YYYY-MM-DD) |
end_date | string | No | End date (YYYY-MM-DD) |
limit | number | No | Max rows to return (default 100) |
offset | number | No | Skip this many rows for pagination (default 0) |
Response includes:
Metadata: period, total_rows, rows_returned, truncated, unique_domains, unique_providers, unique_queries
Summary:
| Field | Description |
|---|---|
top_domains | Top 20 domains with citations count and avg_visibility_score |
by_provider | Each provider with citations count and avg_visibility_score |
Data rows:
| Field | Type | Description |
|---|---|---|
date | string | Timestamp |
provider | string | AI provider |
query_text | string | The tracked query |
url | string | Cited URL |
domain | string | Domain of the cited URL |
title | string | Page title |
position | number | Position in the response |
category | string | Citation category |
visibility_score | number | Visibility score (0–1) |
Try asking:
- "Which URLs are AI models citing for my queries?"
- "What are the top cited domains this month?"
- "Show me competitor domains that appear in AI responses"
Example response:
Top 5 cited domains across all providers (last 30 days):
- example.com — 89 citations (your domain)
- competitor-a.com — 67 citations
- wikipedia.org — 42 citations
- competitor-b.com — 38 citations
- reddit.com — 25 citations
Your domain leads in citations. competitor-a.com is your closest rival, especially on ChatGPT where they get cited 3x more than on other providers.
get_keyword_counts
Get keyword frequency data from AI provider responses.
Parameters:
| Param | Type | Required | Description |
|---|---|---|---|
campaign_id | string | Yes | Campaign ID from list_campaigns |
start_date | string | No | Start date (YYYY-MM-DD) |
end_date | string | No | End date (YYYY-MM-DD) |
limit | number | No | Max rows to return (default 100) |
offset | number | No | Skip this many rows for pagination (default 0) |
Response includes:
Metadata: period, total_rows, rows_returned, truncated, unique_keywords, unique_providers, unique_queries
Summary:
| Field | Description |
|---|---|
by_keyword | Each keyword with total_count and avg_count |
by_provider | Each provider with total_keyword_appearances |
Data rows:
| Field | Type | Description |
|---|---|---|
date | string | Timestamp |
provider | string | AI provider |
query_text | string | The tracked query |
keyword | string | The keyword |
count | number | Occurrence count |
Try asking:
- "What keywords come up most in AI answers about my brand?"
- "Which terms do AI providers associate with my queries?"
- "Show keyword frequency differences between ChatGPT and Gemini"
Example response:
Top keywords in AI responses for your tracked queries this week:
Keyword Count Top Provider affordable 34 ChatGPT enterprise 28 Gemini open-source 22 Perplexity scalable 19 ChatGPT "Affordable" is the most common keyword — AI models are framing your space around pricing. If you want to shift the narrative toward quality or features, this is useful input for your content strategy.
Aurora MCP Server — Setup & Configuration
Connect Aurora Intelligence to Claude Desktop, ChatGPT, Claude Code, Cursor, and other MCP-compatible clients to query your GEO tracking data conversationally.
MCP Server Use Cases & Workflows
Real-world workflow examples for the Aurora MCP server — from weekly reports to competitive analysis.