Build a Bounded SEO Research Assistant with Claude and MCP

An SEO research assistant needs more than access to tools. It needs a specific question, evidence requirements, a stopping rule and an output someone can review.

This guide builds a narrow Claude workflow: investigate whether a small set of publications linking to a competitor deserve further research. RankParse provides the backlink evidence; Claude helps organize it; a person validates the opportunity. This is a proposed workflow with illustrative output, not a benchmark or a report of an actual run.

For a broader discussion of which SEO tasks suit AI, see AI SEO workflows. Here the focus is configuring one repeatable research session.

Define the deliverable before connecting more tools

The deliverable is a shortlist of up to five research candidates, each with an evidence trail and a next check. It is not an automatically approved outreach list.

Write a short brief:

Choose the competitor yourself before running the session. Similar authority scores do not make two companies suitable competitors. Audience, subject matter and the page you are researching matter more.

Connect Claude to RankParse

Use the current MCP setup documentation for your client. The sign-in connector and the API-key endpoint have different setup paths; avoid pasting an API key into a connector URL or a shared prompt.

Once connected, ask Claude to identify the tools it can actually access. A setup guide mentioning a tool does not prove it is enabled in your session. If a required tool is missing, stop and adjust the plan rather than asking the model to invent the result.

The MCP introduction explains the protocol. The important operational distinction here is that tool access supplies data; it does not guarantee its completeness or freshness. RankParse's backlink graph uses quarterly snapshots.

Give the assistant a research contract

Paste a prompt like this, replacing the bracketed fields:

Investigate potential editorial publications for [our domain and resource], compared with [competitor]. Use the connected RankParse tools to retrieve a bounded competitor-gap sample. Begin with no more than 20 candidate domains. Preserve snapshot, partial and scoring indicators where available. Do not rank opportunities solely by authority or link count. Return at most five candidates for manual inspection, showing evidence, relevance hypothesis, missing information and next check. Do not send messages or create a campaign. Stop if the tools cannot establish the required facts; ask before expanding the scope.

This makes the desired behavior inspectable. It does not enforce a hard spending cap by itself. Review tool activity and use available account controls where appropriate; the MCP budgeting guide explains the difference between an intended plan and actual usage.

Inspect the first result before asking for enrichment

Ask Claude to explain what the sample represents. For RankParse's competitor-gap tool, the documented process examines a bounded candidate pool and may return partial or unscored results. See the competitor-gap reference for exact behavior.

Three checks prevent common mistakes:

1. Was the answer partial? A partial sample may still be useful, but it is not an exhaustive list of missing links.
2. Was it scored? An unscored result must not be presented as a valid authority ranking. The tool's placeholder zeroes do not mean all those domains have zero authority.
3. What does absence mean? A domain listed as a gap was not observed linking to your site within the underlying comparison. That is not proof that no link exists anywhere today.

If the comparison is empty, investigate scope and coverage before concluding that you have no opportunities. If the candidates are irrelevant, revisit the competitor choice before buying more enrichment.

Require page evidence before editorial conclusions

A referring domain alone does not show why it linked. A publication may host a tutorial, a company profile, a directory, or user-generated content. The appropriate next step depends on the actual page.

Ask:

For each shortlisted domain, identify a relevant linking page if the available data provides one. Separate the page URL and observed anchor from any interpretation of editorial context. If you have not inspected the live page, say so. Do not infer sponsorship, authorship or audience fit from the domain name alone.

A backlink sample can point you toward a page. Live verification may require you or a separate browsing tool to open it. Use MCP versus AI browsing to distinguish these jobs.

The research brief you should expect

The following output structure uses fictional publications and invented scenarios, not measured findings:

The third row is a valid research result. “Insufficient evidence” is more useful than an invented pitch angle.

Save the brief with the input question, tool outputs, retrieval date and snapshot information. Keep verified observations separate from interpretation. This gives another person a way to challenge the recommendation without repeating the entire conversation.

Make the workflow repeatable

After one useful session, keep the research contract and output columns stable. Changing prompts, competitors, result limits and data sources all at once makes comparisons difficult.

Use a script when you need the same bounded extraction across many domains, explicit failure handling and a consistent file format. Use Claude for interactive interpretation and questions that evolve while you inspect evidence. The Python competitor-gap tutorial covers a compact export workflow.

Do not append an unrelated full site audit to every research session. If the actual question is backlink review, use the dedicated Claude audit workflow. A narrow assistant that produces five defensible research candidates is more useful than a broad one that invents a comprehensive SEO verdict.