Keyword Research

OpenSEO Keyword Research

Goal

Turn seed topics into a prioritized keyword opportunity set using OpenSEO MCP data. The output should help the user decide what to target, what to save, and what to research next.

Required inputs

• projectId
• One or more seed topics, products, pages, competitors, or audience problems
• Optional market/location/language

If projectId is missing, use list_projects first. If the target market/location/language is unclear and would materially affect keyword metrics, ask the user; otherwise use the MCP tool defaults.

Project context

The project-context tools are free and shared with the app and other agents.

1. Call get_project_context first and ground the research in it — the business, the goal, the markets, and the competitors and key pages already saved.
2. This skill needs business_overview and current_goal. If either is empty, run a minimal inline setup: ask the user, or infer from the site and confirm, just enough to fill them, write them back with update_project_context, then continue the research. Never front-load the full interview; suggest seo-project-setup at the end for the rest.
3. Before spending credits, check the research log. If the same research ran within the last 30 days, reuse that result and say so instead of re-buying it.
4. On finish, write back what is durable — a sharpened business_overview or current_goal, competitors that kept appearing in the SERPs via addCompetitors, pages the keywords should land on via addKeyPages — and append a research log entry: { appendResearchLog: { summary: "Keyword research: <seeds/market>. Verdict: <conclusion>" } }.

OpenSEO MCP tools

• research_keywords: primary discovery tool. Use 1-5 seeds per call and prefer 150 results unless the user asks for exhaustive research.
• get_keyword_metrics: hydrate up to 700 known keywords with volume, keyword difficulty (KD), search intent, CPC, and monthly trends in one call. Use it to score candidate or known terms — including the Search Console striking-distance queries from step 1.
• get_ranked_keywords: pull exact ranking keyword rows when a target domain or page is part of the research brief.
• get_search_console_performance: when Search Console is connected, start from the project's real first-party demand — queries already earning impressions and near-ranking ("striking distance") terms. Request a high rowLimit and filter average position 5-20 client-side, since the API sorts by clicks and can't filter by position. Then hydrate those striking-distance queries with get_keyword_metrics to attach difficulty and intent.
• get_serp_results: inspect SERPs for the top candidate terms, especially when intent is ambiguous.
• search_local_businesses, get_local_serp_results, and get_google_business_questions: use for local SEO topics when a business/location radius matters.
• list_saved_keywords: avoid duplicating already-saved work or use existing tags as context.
• save_keywords: save selected keywords only after explicit user confirmation.

Workflow

1. Normalize seeds into a small set of distinct research angles. If Search Console is connected for the project, first pull get_search_console_performance (high rowLimit, default lookback), filter to striking-distance positions (~5–20) client-side, and hydrate those queries with get_keyword_metrics to attach KD and intent. That ranked, hydrated list is your fastest opportunity set — work it before broad discovery.
2. If the request is local SEO, identify the business, location/coordinates or service area, and local categories. Use search_local_businesses and get_local_serp_results for the most important location/keyword set instead of relying only on national keyword/SERP data.
3. Call research_keywords for exploratory seeds. Use bulk calls when possible.
4. Use get_keyword_metrics to hydrate a fixed keyword list — or the striking-distance queries from step 1 — with volume, KD, and intent before prioritizing.
5. Use get_ranked_keywords when the user provides a domain/page and wants opportunities based on current rankings, near-misses, or competitor-owned terms.
6. Remove irrelevant, duplicate, branded-only, and off-intent terms.
7. Prioritize by practical opportunity, not volume alone:
   • Strong match to the user's product/page/topic
   • Clear search intent
   • Reasonable difficulty
   • Useful volume/CPC signal
   • SERP where the user can plausibly compete
   • For local SEO, local-pack/Maps visibility and proximity fit
8. Use get_serp_results for high-potential or ambiguous keywords when SERP intent would change the recommendation; keep the default check small.
9. Present a shortlist and a longer opportunity table.
10. Ask before saving keywords. When saving, suggest concise tags such as topic:<topic>, intent:<intent>, or page:<slug>.

Output format

Start with the highest-signal recommendation:

• Best opportunity theme
• Top keywords to target now
• Keywords to save
• Risks or SERP caveats

Then include a compact table:

End with next actions, including whether to run keyword clustering, create a content brief, or save the chosen keywords.

Guardrails

• Do not invent metrics. If OpenSEO does not return a value, write unknown.
• Do not call save_keywords without explicit confirmation.
• Prefer business-fit and intent-fit over chasing the largest volume term.