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Connect Tool Description Semantic Density Scorer to your AI

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Fix vague capability descriptions to stop agent errors.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Semantic Density Scorer.

  1. 01

    Calculate naming uniformity

    This capability checks if your parameter names follow a consistent casing convention like camelCase or snake_case.

  2. 02

    Get clarity score

    This capability provides a final assessment of how well an LLM will understand the capability based on semantic markers.

  3. 03

    Analyze description linguistics

    This capability measures the actionable quality of your text by calculating verb density.

Real work

What teams actually run

01

Schema Auditing

Run a batch of capability descriptions through the scorer to find weak links in your API definitions.

02

Debugging Agent Failures

When an agent misses a capability call, use the density scorer to see if the description lacks enough verbs.

03

Standardizing Toolsets

Use the naming uniformity capability to ensure a large library of capabilities follows a single casing standard.

04

Optimizing Prompt Engineering

Refine capability descriptions based on the clarity score to maximize model comprehension.

One connector, every AI

Semantic Density Scorer works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Semantic Density Scorer to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

854ms average. Fast in production.

Semantic Density Scorer is checked daily against the live service.

Daily averagePeak 1059ms
Oct 3Today
Fastest day
630ms
Slowest day
1059ms
14-day trend
Improving-17%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Semantic Density Scorer, so you can see the experience inside your AI.

It does not authenticate your account with Semantic Density Scorer. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Semantic Density Scorer Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Semantic Density Scorer capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "tool-description-semantic-density-scorer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_ZgfgQL81tK2KxCGQ3HRK0AigWOuqKt5KVLonvnoZ/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Semantic Density Scorer in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Semantic Density Scorer owners hand off.

This MCP is built for developers building agentic workflows who need reliable capability-calling performance.

  • 01

    AI Engineers

    They use this to audit capability schemas before deploying them to production agents.

  • 02

    Prompt Engineers

    They use this to refine the linguistic structure of capability definitions.

  • 03

    LLM App Developers

    They use this to debug why their agents fail to trigger specific functions.

FAQ

Questions Semantic Density Scorer owners ask.

  • 01

    How does this MCP improve capability calling?

    It identifies descriptions that are too wordy or passive, helping you write more actionable instructions that your agent can follow.

  • 02

    What is instructional density?

    It is a metric calculated by measuring the ratio of verbs to total words in a capability description.

  • 03

    Can I check for snake_case vs camelCase?

    Yes, the calculate_naming_uniformity capability specifically checks if your parameters follow a consistent casing convention.

  • 04

    Which clients can use this MCP?

    You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 05

    Does this help with hallucinated parameters?

    Yes, by ensuring naming uniformity and clarity, you reduce the chance of the agent misinterpreting your schema.

  • 06

    What is verb density?

    Verb density is the ratio of imperative/action verbs to the total word count in a description. High density indicates more direct instructions for the LLM.

  • 07

    How does the clarity score work?

    The clarity score is a composite metric that rewards explicit return-type definitions and penalizes descriptions that are either too brief or too verbose.

  • 08

    Can I check for snake_case consistency?

    Yes, you can use calculate_naming_uniformity to verify if parameter names follow either camelCase or snake_case conventions.

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