MCP For Claude Marketplace
Keyword Proximity Checker

Keyword Proximity Checker MCP Connector for Claude

A+

Analyze text to measure the word distance between keywords for SEO relevance.

3 tools Official Updated Jun 29, 2026 Official Vinkius Partner
More Details Connect to Claude

The Keyword Proximity Checker is an analytical tool designed to assess semantic relevance for search engine optimization. By calculating the exact number of words separating specific keywords, it helps identify topical density and clusters within a text. Use get_word_distance to find the distance between two terms, evaluate_proximity_status to check if pairs meet a threshold, or detect_keyword_clusters to locate high-density keyword groups.

seokeywordsproximitytext-analysistokenization

3 tools expose this connector's capabilities to your AI agent.

evaluate_proximity_status

Determine if specific pairs of keywords meet a predefined proximity threshold

detect_keyword_clusters

Identify clusters where multiple keywords appear near each other

get_word_distance

Calculate the exact number of words separating two specific keywords in a given text

See how to talk to your AI agent using Keyword Proximity Checker.

What is the distance between 'apple' and 'banana' in the text: 'I ate an apple and then a banana.'?

The distance between 'apple' and 'banana' is 3 words.

Check if 'SEO' and 'content' are near in: 'High quality SEO content is vital.' with a max distance of 1.

The pair 'SEO - content' has a status of Near with an actual distance of 0.

Find clusters for ['cat', 'dog'] in: 'The cat and dog played.' with window size 3.

A cluster was found containing ['cat', 'dog'] starting at index 1 and ending at index 3.

The tool calculates the difference between the positions of the keywords and subtracts one. It always finds the shortest possible distance if a keyword appears multiple times.

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