PlainGrade
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@PlainGradeScore the readability of this paragraph: The quick brown fox jumps over the lazy dog."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
PlainGrade
English readability scores (Flesch, Flesch-Kincaid, Fog, SMOG) and text stats. Text never stored.
Live service
Web app and API: https://plaingrade-api.mike-tusa.workers.dev/
Support: digitalpromohub.support@gmail.com
Related MCP server: mcp-textstats
Use it from an AI assistant (MCP)
PlainGrade is a remote MCP server (Streamable HTTP) at https://plaingrade-api.mike-tusa.workers.dev/mcp. Tools: score_readability.
Cursor, Cline and Windsurf accept this config:
{
"mcpServers": {
"plaingrade": {
"type": "http",
"url": "https://plaingrade-api.mike-tusa.workers.dev/mcp"
}
}
}Claude Desktop: open Settings > Connectors, choose "Add custom connector" and paste https://plaingrade-api.mike-tusa.workers.dev/mcp. Or, for clients that only support local (stdio) servers, use the mcp-remote bridge: npx mcp-remote https://plaingrade-api.mike-tusa.workers.dev/mcp.
VS Code uses a servers key instead of mcpServers.
The server.json file is the MCP Registry manifest for this server.
Run your own copy
Requires Node.js 22+ and a Cloudflare account.
npm install
npx wrangler@4 dev # local dev serverwrangler.toml is a template: create your own KV namespaces / D1 databases / rate-limit namespaces and replace the <PLACEHOLDER> values before npx wrangler@4 deploy. Any secrets the Worker reads go in wrangler secret put (or .dev.vars locally), never in the repo.
License
MIT (c) Digital Promo Hub. See LICENSE.
This server cannot be deployed
Maintenance
Related MCP Connectors
English readability scores (Flesch, Flesch-Kincaid, Fog, SMOG) and text stats. Text never stored.
Text statistics & readability MCP.
Scores text for substance, depth, and clarity in under 25ms.
Sentiment, language detection, readability, keywords, summaries and profanity filtering
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