Keyword Extractor Engine Connector for AI agents.
3 live capabilities
Identify core themes and keyword density in your content.
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Why people use Keyword Extractor Engine
Keyword Extractor NLP Analysis for Content Strategy
This Connector changes that by letting your AI client do the heavy lifting in one step. You just point it at the text, and it spits out a ranked list of what actually matters.
What Vinkius changes
You get a clear, data-backed map of the core topics in any text block.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
SEO Density Audit
A marketer asks the agent to check if a blog post is over-optimized for a specific phrase.
- Real-world use case 02
Sentiment Analysis
A researcher wants to know the most common complaints in a list of 500 customer reviews.
- Real-world use case 03
Academic Word Study
A linguist needs to see the frequency of specific technical terms in a set of research papers.
Complete set · 3capabilities
The complete Keyword Extractor Engine capability set.
These are the exact actions your AI can choose when you ask it to work with Keyword Extractor Engine.
01—03
3 capabilities in this set.
Part of 3 available through Keyword Extractor Engine.
- 01 Capability
Rank keywords
Get a prioritized list of significant terms from a text block. This shows you what a document is about at a glance.
- 02 Capability
Calculate term density
See how often a specific word appears relative to the total text to check if you hit your keyword goals.
- 03 Capability
Verify language capability
Check if the Connector handles your language before you start to avoid errors with Portuguese or Spanish text.
Set up in minutes
One URL. Then ask Keyword Extractor Engine to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Keyword Extractor Engine 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_pI6NO6ZkNzeuheRsFlhUgGz8DmheaeJNHApCwOY7/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 Keyword Extractor Engine, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Keyword Extractor Engine for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_pI6NO6ZkNzeuheRsFlhUgGz8DmheaeJNHApCwOY7/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 Keyword Extractor Engine URL.
- Step 03
Save and start
Save the connection and enable Keyword Extractor Engine in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"keyword-extractor": {
"url": "https://edge.vinkius.com/vk_preview_pI6NO6ZkNzeuheRsFlhUgGz8DmheaeJNHApCwOY7/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 Keyword Extractor Engine
Open Agent mode in chat and ask: "Using Keyword Extractor Engine, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"keyword-extractor": {
"url": "https://edge.vinkius.com/vk_preview_pI6NO6ZkNzeuheRsFlhUgGz8DmheaeJNHApCwOY7/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 Keyword Extractor Engine
Ask Copilot: "Using Keyword Extractor Engine, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"keyword-extractor": {
"url": "https://edge.vinkius.com/vk_preview_pI6NO6ZkNzeuheRsFlhUgGz8DmheaeJNHApCwOY7/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 Keyword Extractor Engine
Open Cascade and ask: "Using Keyword Extractor Engine, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"keyword-extractor": {
"url": "https://edge.vinkius.com/vk_preview_pI6NO6ZkNzeuheRsFlhUgGz8DmheaeJNHApCwOY7/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 Keyword Extractor Engine
Ask Cline: "Using Keyword Extractor Engine, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add keyword-extractor --transport http "https://edge.vinkius.com/vk_preview_pI6NO6ZkNzeuheRsFlhUgGz8DmheaeJNHApCwOY7/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 Keyword Extractor Engine
Ask Claude: "Using Keyword Extractor Engine, show me...". 3 tools are ready
Where the request belongs
Work Keyword Extractor Engine can move forward.
This is for content creators, SEO specialists, and data analysts who need to extract hard data from large amounts of text.
SEO Specialist
Checking keyword density for blog posts on a Tuesday afternoon to ensure they meet ranking goals without over-optimizing.
Content Strategist
Identifying the most common themes in customer feedback to inform the next product roadmap.
Data Analyst
Processing large datasets of qualitative survey responses to find recurring trends.
Linguist
Studying word usage and frequency across different languages for academic research.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse Connectors
Context Redundancy Deduplicator
Identify and quantify exact N-gram overlaps across RAG documents to optimize context window usage.
Keyword Intent Classifier
Categorize search keywords by intent, length, and marketing funnel stage.
Cognitive Load Scorer
Quantify the mental effort required to process text by measuring linguistic complexity.
LinkedIn Formatting Density Scanner
Analyze LinkedIn post visual structure, whitespace ratio, and mobile scannability.
Keyword Density Analyzer
Calculate keyword frequency, density percentage, and spatial distribution in text to optimize SEO content.
TF-IDF Vectorizer Engine
Exact Term Frequency-Inverse Document Frequency scores. Stop LLMs from guessing keyword relevance across massive corpuses.
Bring your own AI
Change the model, client or framework. Keep Keyword Extractor Engine connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Keyword Extractor Engine.
The practical details behind the request, access and result.
What does Keyword Extractor do?
Keyword Extractor identifies the most frequent and significant terms in any text you provide. It helps you quickly see what a document is actually about by filtering out common words like 'the' or 'and'.
Does Keyword Extractor work for Spanish?
Yes, the Connector supports English, Portuguese, and Spanish. You can use it to analyze content in any of these three languages.
How does Keyword Extractor handle common words?
It uses built-in stopword lists to automatically ignore common linguistic noise. This ensures your results focus on the words that actually carry meaning.
Can I use Keyword Extractor for SEO?
Yes, it's great for SEO audits. You can use it to check keyword density and ensure your content hits the right marks without over-optimizing.
What happens when I use Keyword Extractor?
Your AI client will process the text and return a ranked list of keywords or a specific density score. It turns messy text into organized data points instantly.
Which languages are supported?
The engine currently supports English (en), Portuguese (pt), and Spanish (es) through hardcoded stopword lists.
How is keyword density calculated?
Density is calculated by dividing the frequency of a specific term by the total count of all valid tokens (words that are not stopwords) in the text.
Can I check if a language is supported before running analysis?
Yes, you can use the verify_language_capability capability to confirm if a specific ISO 63 639-1 code is available for extraction.
One connection away
Give your agent a direct line to Keyword Extractor Engine.
Connect Keyword Extractor Engine once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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