| name | seo-content-suggestions |
| description | Use when analyzing topical authority, clustering a domain's ranked keywords, finding strong, building, weak, and missing topics against organic competitors, calculating a 0-100 Content Score, or recommending five articles with DataForSEO MCP evidence. |
| compatibility | Requires the official DataForSEO MCP server with the DATAFORSEO_LABS module enabled and filesystem write access. |
SEO Content Suggestions
Use Ranked Keywords, Competitors Domain, and Domain Intersection.
Input and scope
Require a target domain; if absent, ask and wait. Normalize a hostname or HTTP(S) URL to lowercase without credentials, port, suffix, trailing dot, or leading www.; reject malformed input. Accept up to five competitors. Default to United States/en; disclose assumptions. Use Google organic and ignore_synonyms: true. Ask before retries, pagination, or extras.
DataForSEO MCP workflow
- Call
dataforseo_labs_google_ranked_keywords for target with limit: 200, organic items, descending volume. Retain keyword, rank_group, URL, ETV, volume, difficulty, and intent.
- Without competitors, call
dataforseo_labs_google_competitors_domain. Exclude target and top domains; retain five by intersections, then organic ETV.
- Per competitor call
dataforseo_labs_google_domain_intersection with target1: competitor, target2: target, intersections: false, organic items, and limit: 200. Deduplicate keywords, retaining competitors.
- Call ranked keywords with
limit: 200 for the first/top competitor. Use median non-null rank_info.main_domain_rank as benchmark.
- Validate statuses; never invent metrics. Report counts and sampling limits.
Cost accounting
Log each call's endpoint and top-level cost USD. Sum unrounded values. Scope: Total cost: x,xx USD (decimal comma, two digits). Include zero; missing cost means incomplete subtotal; name affected calls.
Clusters and status
Normalize case/punctuation and singularize; group by stems, head terms, and meaning. Merge synonyms; split differing intent/audience. Aim for 8-15 clusters.
Classify target and gap clusters in order:
- Missing: competitors rank; target does not.
- Strong: at least five target keywords rank 1-10 and summed ETV exceeds 100/month.
- Building: a target keyword ranks 1-30 but the cluster is not Strong. Flag top-10 clusters that missed a Strong threshold.
- Weak: every target position exceeds 30.
Report count, best/average position, top-10 count, ETV, volume, URLs, competitor coverage, and status per cluster.
Content Score
total_clusters includes all clusters. From top ceil(n/4) target keywords by volume calculate:
avg_position_top_quartile_score = clamp((100 - mean_rank_group) / 99, 0, 1)
content_score = round(50 * strong_clusters/total_clusters + 25 * (1 - missing_clusters/total_clusters) + 25 * avg_position_top_quartile_score)
If clusters or positions are absent, report unavailable.
Five content moves
Select from Missing and Building clusters. Prioritize commercial or transactional keywords with volume above 200 and difficulty below benchmark; break ties by volume, lower difficulty, then related-term breadth. If fewer than five qualify, use nearest candidates and label relaxed conditions.
Provide title, target and related keywords, intent, volume, difficulty, benchmark, status, rationale, and word-count estimate.
Report
Write Markdown with Scope and total cost, summary, score inputs, competitors, cluster matrix, briefs, gaps, limitations, content moves, and call log. Start with local ISO date.
Use the requested root or SEO/; create <root>/<domain>/. Save as <YYYY-MM-DD>_Content-Suggestions_<domain>.md, for example 2026-06-19_Content-Suggestions_example.com.md.
