OpenSEO Keyword Clustering

Goal

Group keywords into page-level clusters and decide which existing or new page should target each cluster. This is a keyword mapping workflow, not just a semantic grouping exercise.

Required inputs

```
projectId
```
A keyword list, saved keyword tag, seed topic, or target domain
Optional existing URLs/pages to map against

If keywords are not provided, use

list_saved_keywords

for saved sets,

research_keywords

for seed discovery, or

get_ranked_keywords

when the user starts from a target domain.

OpenSEO MCP tools

```
list_saved_keywords
```
: fetch an existing keyword set, optionally filtered by tags.
```
research_keywords
```
: expand a seed when the user starts from a topic.
```
get_ranked_keywords
```
: gather exact ranking keywords and URLs when the user starts from a domain or page.
```
get_search_console_performance
```
: when Search Console is connected, pull real queries with
```
dimensions: ["query","page"]
```
to map terms to the pages already earning impressions and to surface cannibalization (one query splitting clicks across multiple URLs).
```
get_serp_results
```
: validate whether keywords belong on the same page by checking SERP overlap and intent.
```
get_local_serp_results
```
: use for local SEO clusters when Maps/local-pack intent should affect page mapping.
```
save_keywords
```
: optionally tag final clusters after user confirmation.

Workflow

Gather the candidate keyword set.
- Use
```
get_search_console_performance
```
  (dimensions
```
["query","page"]
```
  ) when Search Console is connected to start from real queries and the pages already ranking for them.
- Use
```
get_ranked_keywords
```
  for domain/page-driven clustering.
- Use
```
search_local_businesses
```
  and
```
get_local_serp_results
```
  when proximity, local packs, or Google Business results determine whether terms belong on location pages.
Remove duplicates, irrelevant terms, and terms that clearly require a different product or audience.
Build clusters around intent and page type:
- Same SERP intent and similar ranking pages belong together.
- Different intent, buyer stage, or SERP format should be split.
- Similar words do not guarantee the same cluster.
For important borderline terms, use a small
```
get_serp_results
```
batch to check overlap.
Assign each cluster to:
- Existing URL, if supplied and appropriate
- New page recommendation, if no existing page fits
- Do-not-target / later bucket, if weak or off-strategy
Identify cannibalization risk when multiple pages would target the same intent. When Search Console is connected, confirm it from real data with
```
get_search_console_performance
```
(
```
dimensions: ["query","page"]
```
) — the same query sending impressions to multiple URLs.
Ask before applying cluster tags with
```
save_keywords
```
.

Output format

Start with a short mapping summary:

Number of clusters
Pages to create
Existing pages to update
Cannibalization or consolidation issues

Then include:

Cluster	Primary keyword	Secondary keywords	Intent	Target page	Priority	Notes

For each cluster, include a recommended page brief:

Page type
Searcher problem
Required sections
Internal-link opportunities
Save/tag suggestion

Guardrails

Do not over-cluster tiny keyword sets. If there are fewer than 10 usable terms, produce a simple map.
Do not rely on lexical similarity alone. SERP intent wins.
Do not replace tags broadly without explicit confirmation.
If existing URL data is missing, label target pages as proposed.

keyword-clustering

NPX Install

Tags

SKILL.md Content