# Long-Tail Extractor MCP for AI Agents AI Agent Connect > Long-Tail Extractor identifies recurring word sequences (n-grams) to find long-tail keyword candidates in any text. It pulls out 3, 4, and 5-word phrases, counts how often they appear, and measures their density. Use it to spot hidden patterns in large content bodies for better SEO targeting and content planning. ## Overview - **Category:** seo - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_C9KvCRnQRkMIt9JmZl1RL6gQADHKTCr9uzYj4nO7/ai-agent-connect - **Tags:** n-grams, keywords, text-analysis, seo-tools, pattern-recognition, data-mining ## Description Instead of scrolling through pages of copy to see which phrases stick, you can now ask your agent to pull out every three-to-five-word sequence that repeats. This Connector is built for the heavy lifting of text mining. If you're trying to figure out what your audience actually says or which phrases are dominating your blog posts, it does the counting for you. It helps you spot those specific, low-competition phrases that usually get buried in manual reviews. You can set rules to only see the most common patterns or check how often a specific phrase shows up compared to the rest of your content. It takes the guesswork out of content audits. Since it's part of the Vinkius catalog, you can plug it into your existing workflow to turn raw text into a structured list of keyword opportunities. It's about moving from "I think we say this a lot" to "We say this exactly 42 times in this specific section." ## Tools ### calculate_pattern_density Shows you what percentage of your total text is made up of a specific recurring phrase. This helps measure content balance. ### extract_ngram_sequences Scans your text to find and count every 3, 4, and 5-word phrase it finds. This helps you identify recurring patterns instantly. ### filter_high_frequency_patterns Removes any phrases that don't meet your minimum count. Use this to focus on the most common data points. ## Prompt Examples **Prompt:** ``` Find all 3-word phrases that appear more than twice in this review: 'The battery life is great. The battery life is long. I love the battery life.' ``` **Response:** ``` I found one recurring 3-word phrase: **the battery life** (3 occurrences). ``` **Prompt:** ``` Calculate the density of the phrase 'easy to use' in a 500-word instruction manual where it appears 10 times. ``` **Response:** ``` The density score for **easy to use** is **0.02**. ``` **Prompt:** ``` Filter these sequences to show only those appearing at least 4 times: [{'phrase': 'best in class', 'count': 2}, {'phrase': 'very reliable', 'count': 5}, {'phrase': 'fast shipping', 'count': 1}] ``` **Response:** ``` The following patterns met your threshold: **very reliable**. ``` ## Capabilities ### Identify recurring phrases Find 3, 4, and 5-word sequences automatically within any body of text. ### Filter by frequency Isolate only the patterns that meet your specific count requirements to cut out the noise. ### Measure phrase density See what percentage of your total text is made up of a specific recurring phrase. ### Spot long-tail keywords Uncover specific phrases that are often missed by standard, broader keyword tools. ### Automate content audits Scan large bodies of text for consistent messaging or repetitive language in seconds. ## Use Cases ### Audit a blog library An SEO manager asks the agent to find every 4-word phrase appearing more than 5 times across 50 articles to check for brand consistency. ### Analyze customer reviews A product manager uses the agent to scan 1,000 reviews and identify the most common 3-word phrases customers use to describe a product. ### Refine ad copy A copywriter asks the agent to check the density of a specific call-to-action phrase to see if it's overused in a landing page. ### Content gap analysis A strategist scans a competitor's page to see which long-tail sequences they are prioritizing and then adjusts their own content. ## Benefits - Stop guessing which phrases are popular by using extract_ngram_sequences to get exact counts and positions. - Focus only on what matters by using filter_high_frequency_patterns to cut out the noise from your data. - Get a better sense of content balance by using calculate_pattern_density to see how much space specific phrases take up. - Find hidden SEO opportunities in large documents that standard keyword tools might overlook. - Save hours of manual auditing by letting your agent scan entire content libraries in seconds. ## How It Works The bottom line is you get a data-backed list of recurring phrases without having to read through every single word yourself. 1. Provide your AI client with a block of text or a file content. 2. Instruct the agent to scan for n-grams and filter by your desired frequency. 3. Receive a structured list of phrases with counts, positions, and density scores. ## Frequently Asked Questions **What is the Long-Tail Extractor MCP for?** It helps you find repeating word sequences in your text to discover long-tail keywords for SEO and content strategy. **Can I use the Long-Tail Extractor MCP to find brand consistency?** Yes, you can scan your content to see how often specific brand phrases appear across different pages. **Does the Long-Tail Extractor MCP work for customer reviews?** It's perfect for scanning large amounts of feedback to find common 3, 4, or 5-word phrases customers use. **How does the Long-Tail Extractor MCP help with SEO?** It identifies specific long-tail phrases that are often missed by broader keyword tools but are highly relevant to your audience. **Can I filter the results with the Long-Tail Extractor MCP?** Yes, you can set a minimum frequency so your agent only shows you the most common patterns. **What kind of phrases does the Long-Tail Extractor MCP find?** It specifically looks for contiguous blocks of 3, 4, and 5 words to identify meaningful sequences. **Will the Long-Tail Extractor MCP help me with content audits?** It automates the tedious part of auditing content by providing precise data on phrase frequency and location. **What are n-grams?** N-grams are contiguous sequences of $n$ items from a given sample of text. In this tool, we focus on sequences of 3, 4, and 5 words. **How can I use `extract_ngram_sequences`?** Provide the raw text you want to analyze via the `sourceText` parameter. You can also specify a minimum and maximum n-gram size. **What is the purpose of density calculation?** The `calculate_pattern_density` tool calculates how often a phrase appears relative to the total word count, helping you distinguish significant patterns from isolated occurrences.