How to Use the Deterministic Readability Scorer MCP in Claude

Q: How does Deterministic Readability Scorer run inside Claude Desktop?

You configure the server in your local claudedesktopconfig.json file. This lets Claude Desktop call calculatefleschkincaid and other math tools as local subprocesses using a local MCP server in your config.

Q: Does Deterministic Readability Scorer in Claude Desktop support custom reading speeds?

Yes. The calculatereadingtime tool accepts an optional words-per-minute parameter directly from your chat interface. This allows you to tailor the output to fast or slow readers.

Get deterministic readability scores directly in Claude Desktop without letting your AI agent guess at grade levels.

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Connect Deterministic Readability Scorer MCP to Claude Desktop

Create your Vinkius account to connect Deterministic Readability Scorer to Claude Desktop and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Deterministic Readability Scorer with Claude Desktop

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Run Flesch-Kincaid calculations locally

The `calculate_flesch_kincaid` tool gives Claude Desktop the math it needs to analyze text complexity. Stop letting your AI client guess if a draft is readable. This tool parses the actual syllables and sentence structures directly on your local machine, returning a precise, reproducible grade level. When you run this via the desktop app, the process stays local. You feed the raw text directly from your open editor, and the MCP Server spits back a hard number. It is pure math, not a subjective LLM opinion.

Evaluate clarity using Gunning Fog metrics

The `calculate_gunning_fog` tool calculates the exact index of your document to flag overly complex sentences. Instead of relying on vague prompts to make it simpler, your AI client uses this tool to locate dense, hard-to-read paragraphs. This helps editors analyze technical drafts or copy before publishing. Whether you connect via local stdio or use a remote MCP server URL, the math remains exactly the same.

Calculate exact reading times in Claude Desktop

The `calculate_reading_time` tool measures word counts and returns exact estimates. You can pass a custom words-per-minute speed or let the tool default to 200. Content teams use this to automate newsletter layouts. Your AI client reads the raw text, runs the math, and inserts the result directly.

Setup guide

Set up Deterministic Readability Scorer MCP in Claude Web or Desktop

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.
3

Start a conversation

Open a new chat. The Deterministic Readability Scorer MCP tools are available immediately — no restart needed.

Endpoint URL

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

No configuration file needed — paste the URL directly in the Claude web interface.

Available on Free (1 connector), Pro, Max, Team, and Enterprise plans.

Prerequisites

Claude Desktop installed (macOS or Windows)
Active Vinkius subscription with a valid endpoint token

1

Open Claude Desktop Settings

Click the menu icon at the top-left corner, go to Settings → Developer → Edit Config. This opens claude_desktop_config.json in your default text editor.
2

Paste the Deterministic Readability Scorer MCP configuration

Copy the JSON snippet on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Desktop

Close and reopen the application. Claude needs a full restart to load new MCPs — refreshing a conversation is not enough.
4

Verify the connection

Open a new conversation. Click the 🔌 icon at the bottom of the message input. You should see tools listed under deterministic-readability-scorer-mcp.

json

{
  "mcpServers": {
    "deterministic-readability-scorer-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by readability-scorer. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Deterministic Readability Scorer MCP in Claude Desktop

You configure the server in your local claude_desktop_config.json file. This lets Claude Desktop call `calculate_flesch_kincaid` and other math tools as local subprocesses using a local MCP server in your config.

Yes. When configured as a local stdio connection inside Claude Desktop, the server runs entirely on your machine. It does not require an active internet connection to parse your documents.

Yes. The `calculate_reading_time` tool accepts an optional words-per-minute parameter directly from your chat interface. This allows you to tailor the output to fast or slow readers.

LLMs are notoriously bad at counting syllables and sentences. This server uses rigid mathematical algorithms to guarantee your scores are 100% accurate and reproducible.

No. When running locally via stdio, your text strings never leave your machine. Vinkius runs the server in an isolated sandbox, keeping your proprietary documentation completely private.

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