OpenSEO Keyword Research

---
name: keyword-research
description: "Discover keyword opportunities, evaluate metrics and SERPs, and save/tag promising terms."
---

# 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.

## 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:

| Keyword | Intent | Volume |  KD | CPC | Priority | Notes |
| ------- | ------ | -----: | --: | --: | -------- | ----- |

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.