Prompt Entropy and Clarity Scorer Connector for AI agents.
3 live capabilities
Measure linguistic complexity and cognitive load for better prompt engineering
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Why people use Prompt Entropy and Clarity Scorer
Stop guessing with Prompt Entropy and Clarity Scorer linguistic diagnostics
With this MCP, you replace guesswork with data. You get a clear view of the structural complexity of your instructions. You'll know exactly when a prompt crosses the line from 'clear' to 'overwhelming,' allowing you to fix the problem before it ever hits production.
What Vinkius changes
You get a mathematical way to prove your prompts are actually clear.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Debugging failing agent instructions
An engineer notices an agent is ignoring constraints.
- Real-world use case 02
Optimizing system prompts for scale
A developer wants to minimize token usage and latency.
- Real-world use case 03
A/B testing prompt variations
A researcher compares two versions of a prompt.
Complete set · 3capabilities
The complete Prompt Entropy and Clarity Scorer capability set.
These are the exact actions your AI can choose when you ask it to work with Prompt Entropy and Clarity Scorer.
01—03
3 capabilities in this set.
Part of 3 available through Prompt Entropy and Clarity Scorer.
- 01 Capability
Analyze prompt metrics
Extracts raw linguistic data like sentence length and vocabulary variety. It provides the foundational numbers needed to understand text structure.
- 02 Capability
Calculate cognitive load
Converts linguistic metrics into a normalized difficulty score. This tells you exactly how much mental effort the model needs to process the prompt.
- 03 Capability
Summarize prompt health
Combines all metrics into a single readable report. It gives you a high-level view of whether your prompt is optimized or overly complex.
Set up in minutes
One URL. Then ask Prompt Entropy and Clarity Scorer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Prompt Entropy and Clarity Scorer 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_qLECmvvMWFcBjLLe4R2ILHF45rWK79xtC7nGqdaM/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 Prompt Entropy and Clarity Scorer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Prompt Entropy and Clarity Scorer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_qLECmvvMWFcBjLLe4R2ILHF45rWK79xtC7nGqdaM/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 Prompt Entropy and Clarity Scorer URL.
- Step 03
Save and start
Save the connection and enable Prompt Entropy and Clarity Scorer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-entropy-and-clarity-scorer": {
"url": "https://edge.vinkius.com/vk_preview_qLECmvvMWFcBjLLe4R2ILHF45rWK79xtC7nGqdaM/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 Prompt Entropy and Clarity Scorer
Open Agent mode in chat and ask: "Using Prompt Entropy and Clarity Scorer, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-entropy-and-clarity-scorer": {
"url": "https://edge.vinkius.com/vk_preview_qLECmvvMWFcBjLLe4R2ILHF45rWK79xtC7nGqdaM/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 Prompt Entropy and Clarity Scorer
Ask Copilot: "Using Prompt Entropy and Clarity Scorer, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-entropy-and-clarity-scorer": {
"url": "https://edge.vinkius.com/vk_preview_qLECmvvMWFcBjLLe4R2ILHF45rWK79xtC7nGqdaM/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 Prompt Entropy and Clarity Scorer
Open Cascade and ask: "Using Prompt Entropy and Clarity Scorer, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"prompt-entropy-and-clarity-scorer": {
"url": "https://edge.vinkius.com/vk_preview_qLECmvvMWFcBjLLe4R2ILHF45rWK79xtC7nGqdaM/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 Prompt Entropy and Clarity Scorer
Ask Cline: "Using Prompt Entropy and Clarity Scorer, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add prompt-entropy-and-clarity-scorer --transport http "https://edge.vinkius.com/vk_preview_qLECmvvMWFcBjLLe4R2ILHF45rWK79xtC7nGqdaM/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 Prompt Entropy and Clarity Scorer
Ask Claude: "Using Prompt Entropy and Clarity Scorer, show me...". 3 tools are ready
Where the request belongs
Work Prompt Entropy and Clarity Scorer can move forward.
This is for anyone building reliable instruction sets where precision is the difference between a successful task and a hallucination.
Prompt Engineer
Validating that new versions of complex system prompts don't accidentally increase cognitive load.
AI Developer
Testing the linguistic stability of instructions used in automated agent workflows.
LLM Researcher
Analyzing the relationship between sentence structure and model response accuracy.
Build the capability set
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Box
Store, share, and collaborate on files securely with enterprise-grade cloud content management and governance controls.
Bring your own AI
Change the model, client or framework. Keep Prompt Entropy and Clarity Scorer connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
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Amazon Q -
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LM Studio -
AnythingLLM -
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Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Prompt Entropy and Clarity Scorer.
The practical details behind the request, access and result.
How can the Prompt Entropy and Clarity Scorer help my AI agents?
It helps your agents by ensuring the instructions you give them are easy to process. By reducing cognitive load, you reduce the chance of the agent getting confused or ignoring your constraints.
Can I use Prompt Entropy and Clarity Scorer with Claude or Cursor?
Yes. Since this is an MCP, you can connect it to any compatible client like Claude, Cursor, or Windsurf to run diagnostics directly within your existing workflow.
What is cognitive load in the context of Prompt Entropy and Clarity Scorer?
Cognitive load is a score that represents how much 'mental effort' a model must exert to parse your text. Higher scores mean the prompt is more complex and harder for the model to follow.
Does Prompt Entropy and Clarity Scorer work for long system prompts?
Yes, it is specifically designed for this. It is most useful when you have long, complex instructions where structural issues can easily lead to model errors.
Is this MCP useful for automated prompt testing?
Absolutely. You can use the scoring capabilities to programmatically evaluate whether changes to your prompts make them more or less complex, allowing for data-driven optimization.
What does the cognitive load score represent?
The score is a normalized metric that combines lexical diversity, sentence length, and clause density to estimate the total processing difficulty for an LLM.
How can I see the raw linguistic data?
You can use the analyze_prompt_metrics capability to retrieve the Type-Token Ratio, average sentence length, and clause density.
Is this capability compatible with Claude Desktop?
Yes, this MCP server is compatible with Claude Desktop, Cursor, VS Code, Windsurf, and any other MCP-compatible client via Vinkius Edge.
One connection away
Give your agent a direct line to Prompt Entropy and Clarity Scorer.
Connect Prompt Entropy and Clarity Scorer once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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