Deterministic Readability Scorer MCP Server for CursorGive Cursor instant access to 3 tools to Calculate Flesch Kincaid, Calculate Gunning Fog, Calculate Reading Time

Name: Deterministic Readability Scorer
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

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Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

Ask AI about this MCP Server for Cursor

Open in ChatGPT Open in Claude Open in Perplexity

The Deterministic Readability Scorer MCP Server for Cursor is a standout in the Productivity category — giving your AI agent 3 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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ChatGPT

Cursor

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VS Code

JetBrains

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+ other MCP clients

Classic Setup·json

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

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About Deterministic Readability Scorer MCP Server

AI models perceive text as 'tokens', not as phonetic syllables or strict sentence boundaries. Because of this, asking an LLM to calculate a Flesch-Kincaid readability score directly will always result in a mathematical hallucination. The Readability Scorer MCP solves this by routing text analysis through a deterministic V8 Javascript engine.

Cursor's Agent mode turns Deterministic Readability Scorer into an in-editor superpower. Ask Cursor to generate code using live data from Deterministic Readability Scorer and it fetches, processes, and writes. all in a single agentic loop. 3 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

The Superpowers

Flesch-Kincaid Precision: Automatically extracts total syllables, words, and sentences to provide mathematically perfect Reading Ease and Grade Level scores.
Gunning Fog Index: Determines the complexity of your text by algorithmically scanning for polysyllabic words (3+ syllables).
Exact Reading Time: Instead of guessing, it calculates the exact chronological reading time (minutes and seconds) based on a configurable WPM (Words Per Minute).
Zero-Dependency Architecture: Pure Javascript runtime execution means absolute processing speed with no external bloated packages.

The Deterministic Readability Scorer MCP Server exposes 3 tools through the Vinkius. Connect it to Cursor in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 3 Deterministic Readability Scorer tools available for Cursor

When Cursor connects to Deterministic Readability Scorer through Vinkius, your AI agent gets direct access to every tool listed below — spanning text-analysis, flesch-kincaid, linguistic-analysis, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

calculate

Calculate flesch kincaid on Deterministic Readability Scorer

Provide the full text string. Analyzes text readability using the deterministic Flesch-Kincaid algorithm

calculate

Calculate gunning fog on Deterministic Readability Scorer

Provide the full text string. Analyzes text readability using the deterministic Gunning Fog index algorithm

calculate

Calculate reading time on Deterministic Readability Scorer

Provide the text and optionally the Words Per Minute (WPM) speed (defaults to 200). Provides an exact reading time estimation based on word count and WPM

Connect Deterministic Readability Scorer to Cursor via MCP

Follow these steps to wire Deterministic Readability Scorer into Cursor. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"

Add the server config

Paste the JSON configuration above into the mcp.json file that opens

Save the file

Cursor will automatically detect the new MCP server

Start using Deterministic Readability Scorer

Open Agent mode in chat and ask: "Using Deterministic Readability Scorer, help me...". 3 tools available

Why Use Cursor with the Deterministic Readability Scorer MCP Server

Cursor AI Code Editor provides unique advantages when paired with Deterministic Readability Scorer through the Model Context Protocol.

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

Deterministic Readability Scorer + Cursor Use Cases

Practical scenarios where Cursor combined with the Deterministic Readability Scorer MCP Server delivers measurable value.

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

Example Prompts for Deterministic Readability Scorer in Cursor

Ready-to-use prompts you can give your Cursor agent to start working with Deterministic Readability Scorer immediately.

"What is the Flesch-Kincaid Grade Level of my latest blog post?"

"How many minutes will it take a user to read this newsletter?"

"Analyze this legal contract using the Gunning Fog Index."

Troubleshooting Deterministic Readability Scorer MCP Server with Cursor

Common issues when connecting Deterministic Readability Scorer to Cursor through Vinkius, and how to resolve them.

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

Deterministic Readability Scorer + Cursor FAQ

Common questions about integrating Deterministic Readability Scorer MCP Server with Cursor.

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design. tool calls require user visibility and approval.

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.