# What SEO Metrics Does Open‑SEO Track? A Complete Guide to Every Data Point

> Explore Open-SEO's comprehensive tracking of 8 SEO metric categories including keyword research, site audits, backlink analysis, and rank tracking. Discover every data point.

- Repository: [Every App/open-seo](https://github.com/every-app/open-seo)
- Tags: deep-dive
- Published: 2026-08-13

---

**Open‑SEO tracks eight categories of SEO metrics spanning keyword research, site audits, backlink analysis, domain overview, rank tracking, saved keywords, AI brand visibility, and AI search prompt exploration—all powered by DataForSEO's API via an extensible MCP tool architecture.**

The open-source Open‑SEO platform (every-app/open-seo) aggregates a comprehensive suite of search-engine-optimization metrics across its six core features. These metrics are defined centrally in the UI configuration and populated at runtime by a collection of DataForSEO MCP (Model Context Protocol) tools that standardize data retrieval across the stack.

## Keyword Research Metrics

Open‑SEO's **keyword research** feature surfaces traditional search-intelligence data. According to the source code in [`web/src/lib/feature-pages.ts`](https://github.com/every-app/open-seo/blob/main/web/src/lib/feature-pages.ts) (lines 81-86), the metrics include:

- **Search volume** – monthly query frequency
- **Keyword difficulty (KD)** – competitiveness score
- **CPC** – cost-per-click advertising data
- **SERP results** – competitive landscape overview

The `get_keyword_metrics` MCP tool hydrates up to 700 keywords per call with volume, KD, intent, CPC, competition, and optional monthly trending data. The implementation lives in [`src/server/mcp/tools/dataforseo-research-tools.ts`](https://github.com/every-app/open-seo/blob/main/src/server/mcp/tools/dataforseo-research-tools.ts), which delegates to `fetchKeywordMetricsForList` in [`src/server/lib/dataforseo/keyword-metrics.ts`](https://github.com/every-app/open-seo/blob/main/src/server/lib/dataforseo/keyword-metrics.ts) (lines 71-86).

```typescript
// Example: ask the MCP for metrics on a list of keywords
import { callMcpTool } from '@/client/mcp';

async function getMetrics() {
  const response = await callMcpTool('get_keyword_metrics', {
    projectId: 'proj_123',
    keywords: ['open source SEO', 'keyword research tool'],
    includeClickstreamData: true,
    includeMonthlyTrends: false,
    sortBy: 'search_volume',
  });

  // Structured rows available via response.structuredContent.keywords
  console.log('Metrics table:\n', response.text);
}

```

## Site Audit Metrics

The **site audit** feature captures technical SEO health signals. Per [`feature-pages.ts`](https://github.com/every-app/open-seo/blob/main/feature-pages.ts) (lines 92-97), tracked metrics include:

- **Crawled URLs** – total pages discovered
- **Page fields** – titles, meta descriptions, headings
- **Affected pages** – URLs with identified issues
- **Audit history** – temporal change tracking

Data flows through two paths: crawl jobs store page-level signals in the database, while Lighthouse performance data is injected via the `lighthouse` server function (see [`src/server/lib/lighthouseStoredPayload.ts`](https://github.com/every-app/open-seo/blob/main/src/server/lib/lighthouseStoredPayload.ts)).

## Backlink Profile Metrics

**Backlinks** are tracked via [`feature-pages.ts`](https://github.com/every-app/open-seo/blob/main/feature-pages.ts) (lines 64-70) with these dimensions:

- **Backlinks** – total inbound link count
- **Referring domains** – unique source sites
- **Target URLs** – specific destination pages
- **Rank & spam signals** – quality indicators

The `get_backlinks_profile` and `get_backlinks_overview` MCP tools call DataForSEO's backlink endpoints. Implementation resides in [`src/server/mcp/tools/dataforseo-research-tools.ts`](https://github.com/every-app/open-seo/blob/main/src/server/mcp/tools/dataforseo-research-tools.ts).

## Domain Overview Metrics

For competitive intelligence, **domain overview** (lines 41-46 in [`feature-pages.ts`](https://github.com/every-app/open-seo/blob/main/feature-pages.ts)) tracks:

- **Organic traffic** – estimated monthly visits
- **Organic keywords** – ranking term count
- **Top keywords** – highest-value ranking queries
- **Top pages** – most visible URLs

The `get_domain_overview` MCP tool queries DataForSEO Labs for these estimates.

## Rank Tracking Metrics

The **rank tracking** feature (lines 50-55) monitors positional performance:

- **Desktop rank** – search position on desktop
- **Mobile rank** – search position on mobile
- **SERP features** – presence in rich results
- **Position change** – historical delta

`get_rank_tracker` stores periodic checks, with refresh logic in [`src/server/functions/rank-tracking.ts`](https://github.com/every-app/open-seo/blob/main/src/server/functions/rank-tracking.ts) and full service implementation in [`src/server/features/rank-tracking/services/RankTrackingService.ts`](https://github.com/every-app/open-seo/blob/main/src/server/features/rank-tracking/services/RankTrackingService.ts).

## Saved Keywords Metrics

For **saved keywords** (lines 98-103), the UI displays:

- **Saved ideas** – bookmarked research terms
- **Tags** – user-defined categorization
- **Volume** – last known search frequency
- **Difficulty** – last known KD score

These metrics persist from the initial `get_keyword_metrics` hydration call.

## AI Brand Visibility Metrics

Open‑SEO uniquely tracks **AI brand visibility** (lines 70-75) with:

- **Mentions** – brand appearances in AI responses
- **Citations** – referenced sources
- **Platforms** – which AI systems surface the brand
- **Cited domains** – competitor citation analysis

The `get_ai_brand_visibility` MCP tool queries DataForSEO's AI-optimization endpoints.

## AI Search Prompt Explorer Metrics

The **AI search prompt explorer** (lines 76-81) captures:

- **Prompts** – tested query variations
- **Web context** – sources cited in responses
- **Search-country** – geographic settings
- **Brand mentions** – visibility in AI answers

The `ai_search_prompts` MCP tool executes identical prompts across supported models and returns citation URLs for comparison.

## Architectural Flow: How Metrics Propagate

Understanding **how Open‑SEO metrics flow** from definition to display requires tracing three layers:

1. **Metric definitions** – Static labels and UI grouping in [`web/src/lib/feature-pages.ts`](https://github.com/every-app/open-seo/blob/main/web/src/lib/feature-pages.ts); each feature's `metrics` array drives [`components/feature-page.tsx`](https://github.com/every-app/open-seo/blob/main/components/feature-page.tsx)

2. **MCP tool layer** – Server-side tools expose raw DataForSEO calls with standardized transforms (snake_case via `toMcpKeywordMetricRow`)

3. **Data retrieval** – Client creation through `createDataforseoClient`, with optional clickstream enrichment and configurable `sortBy` parameters

For direct server-side access without the MCP abstraction:

```typescript
import { createDataforseoClient } from '@/server/lib/dataforseo';
import { fetchKeywordMetricsForList } from '@/server/lib/dataforseo/keyword-metrics';

async function fetchDirectly() {
  const client = createDataforseoClient({ /* billing context */ });
  const metrics = await fetchKeywordMetricsForList(client, {
    keywords: ['site audit', 'backlink analysis'],
    locationCode: 2840,           // US
    languageCode: 'en',
    creditFeature: 'keyword_research',
  });
  console.log(metrics); // array of MetricRow objects
}

```

## Summary

- **Eight metric categories** cover traditional SEO (keywords, backlinks, ranks), technical health (site audits), competitive intelligence (domain overview), and emerging AI-search visibility
- **Centralized configuration** in [`web/src/lib/feature-pages.ts`](https://github.com/every-app/open-seo/blob/main/web/src/lib/feature-pages.ts) defines all metric labels and groupings
- **MCP tool architecture** standardizes DataForSEO API access across [`dataforseo-research-tools.ts`](https://github.com/every-app/open-seo/blob/main/dataforseo-research-tools.ts) and related server modules
- **Dual output format** returns both human-readable tables and structured JSON for programmatic consumption
- **Extensible design** allows new metric dimensions by adding feature definitions and corresponding MCP tools

## Frequently Asked Questions

### What data provider powers Open‑SEO's metrics?

All metrics originate from **DataForSEO's API**, accessed through a custom MCP tool layer that standardizes authentication, transforms, and caching. The `createDataforseoClient` factory manages credential context and rate limiting.

### Can I export raw metric data from Open‑SEO?

Yes. MCP tool responses include `structuredContent` with typed arrays (e.g., `keywords: MetricRow[]`). For direct programmatic access, use server functions like `fetchKeywordMetricsForList` which return native TypeScript objects.

### How does Open‑SEO track AI-specific SEO metrics?

Two dedicated features monitor AI-search visibility: `get_ai_brand_visibility` tracks brand mentions across AI platforms, while `ai_search_prompts` executes controlled prompt testing across multiple models and captures their citation behavior.

### Where are metric definitions stored if I want to customize the dashboard?

Edit [`web/src/lib/feature-pages.ts`](https://github.com/every-app/open-seo/blob/main/web/src/lib/feature-pages.ts) to modify metric labels, groupings, or add new features. The [`feature-page.tsx`](https://github.com/every-app/open-seo/blob/main/feature-page.tsx) component automatically renders any feature with a valid `metrics` array declaration.