N-gram Frequency Analyzer Connector for AI agents.
3 live capabilities
Analyze linguistic patterns and text complexity with statistical N-gram data
Waiting for input…
Why people use N-gram Frequency Analyzer
Stop guessing about text repetition with N-gram Frequency Analyzer
With this MCP, you stop guessing. You can ask your agent to pull the exact frequency of specific word sequences or identify the most common patterns in a document. You get a data-driven view of how a text is actually built.
What Vinkius changes
You get instant, mathematical proof of a text's structural patterns.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Detecting repetitive brand voice
An editor uses compute_ngram_frequencies to see if a writer is leaning too heavily on specific buzzwords or repetitive sentence starters.
- Real-world use case 02
Evaluating educational content
A curriculum designer uses assess_linguistic_diversity to ensure a textbook's reading level matches the target age group.
- Real-world use case 03
NLP dataset validation
A data scientist uses extract_top_patterns to check for biased or overly frequent patterns in a training corpus.
Complete set · 3capabilities
The complete N-gram Frequency Analyzer capability set.
These are the exact actions your AI can choose when you ask it to work with N-gram Frequency Analyzer.
01—03
3 capabilities in this set.
Part of 3 available through N-gram Frequency Analyzer.
- 01 Capability
Assess linguistic diversity
Categorizes text into complexity tiers based on its linguistic variety. It helps you understand if a text is too simple or too dense.
- 02 Capability
Compute ngram frequencies
Provides a detailed breakdown of how often specific N-grams appear. Use this to get exact counts of recurring word sequences.
- 03 Capability
Extract top patterns
Quickly identifies the most frequent sequences in a text. This lets you find dominant patterns without processing the whole dataset.
Set up in minutes
One URL. Then ask N-gram Frequency Analyzer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use N-gram Frequency Analyzer from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_3AzBZIrhX06RFCONh5nmasWdxskAtoiwPPesbk87/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it N-gram Frequency Analyzer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable N-gram Frequency Analyzer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_3AzBZIrhX06RFCONh5nmasWdxskAtoiwPPesbk87/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the N-gram Frequency Analyzer URL.
- Step 03
Save and start
Save the connection and enable N-gram Frequency Analyzer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"n-gram-frequency-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_3AzBZIrhX06RFCONh5nmasWdxskAtoiwPPesbk87/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using N-gram Frequency Analyzer
Open Agent mode in chat and ask: "Using N-gram Frequency Analyzer, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"n-gram-frequency-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_3AzBZIrhX06RFCONh5nmasWdxskAtoiwPPesbk87/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using N-gram Frequency Analyzer
Ask Copilot: "Using N-gram Frequency Analyzer, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"n-gram-frequency-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_3AzBZIrhX06RFCONh5nmasWdxskAtoiwPPesbk87/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using N-gram Frequency Analyzer
Open Cascade and ask: "Using N-gram Frequency Analyzer, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"n-gram-frequency-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_3AzBZIrhX06RFCONh5nmasWdxskAtoiwPPesbk87/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using N-gram Frequency Analyzer
Ask Cline: "Using N-gram Frequency Analyzer, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add n-gram-frequency-analyzer --transport http "https://edge.vinkius.com/vk_preview_3AzBZIrhX06RFCONh5nmasWdxskAtoiwPPesbk87/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using N-gram Frequency Analyzer
Ask Claude: "Using N-gram Frequency Analyzer, show me...". 3 tools are ready
Where the request belongs
Work N-gram Frequency Analyzer can move forward.
This is for professionals who need to verify the quality, style, or complexity of written content through data rather than intuition.
Linguistic Researcher
Analyzing corpus data to find recurring patterns in specific dialects or writing styles.
Content Strategist
Checking if brand voice remains consistent by monitoring word sequence variety.
NLP Engineer
Validating text datasets for diversity and pattern density before training models.
Editor
Identifying repetitive phrasing or overly complex sentence structures in long-form manuscripts.
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Bring your own AI
Change the model, client or framework. Keep N-gram Frequency Analyzer connected.
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Before you connect
Questions about N-gram Frequency Analyzer.
The practical details behind the request, access and result.
How can I use the N-gram Frequency Analyzer to check my writing?
You can use it to find repetitive phrases or check if your vocabulary is diverse enough. It gives you exact counts of how often you use certain word sequences.
Can the N-gram Frequency Analyzer help with reading levels?
Yes. It can categorize text into different complexity tiers, helping you see if your writing is too simple or too difficult for your target audience.
Is the N-gram Frequency Analyzer useful for large datasets?
It is very useful for finding patterns in large amounts of text without you having to read through everything manually.
How does the N-gram Frequency Analyzer compare to a standard spellchecker?
A spellchecker looks for mistakes. This MCP looks for patterns, repetition, and structural complexity, giving you a mathematical view of your writing style.
Can I use the N-gram Frequency Analyzer with Claude or Cursor?
Yes, you can connect this MCP to any compatible client like Claude, Cursor, or Windsurf through Vinkius to perform text analysis directly in your chat.
How can I find the most frequent word sequences?
Use the extract_top_patterns capability to identify top N-grams.
Is this analyzer compatible with all languages?
No, it is specifically designed for English text processing.
How is text complexity measured?
Complexity is determined by the diversity ratio provided by assess_linguistic_diversity.
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