About Naturalmelo MCP
Naturalmelo MCP is a lightweight server for writers and editors who want to find AI-template patterns in text. It combines a local rule-based scan with an optional OpenAI-compatible LLM pass and returns flagged excerpts with rewrite hints.
Key features
- 01Rule-based text pattern scan
- 02Optional LLM analysis with own key
- 03Naturalness score and label
- 04Flagged excerpts with rewrite hints
- 05General and academic modes
Use cases
- 01Review draft text for template-like phrasing
- 02Find filler transitions in an article
- 03Check academic text with tailored rules
MCP support
Exposes the `check_ai_content` tool to MCP clients. It scans text locally by default and can optionally use an OpenAI-compatible endpoint when configured with an API key.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEnaturalmelo-mcp
Lightweight MCP server for AI content detection — detects AI-template patterns in text.
One tool only:
check_ai_content
How it works
- Rule-based scan (always runs, no API key needed) — 5 built-in pattern rules covering generic openings, hollow claims, filler transitions, stacked connectors, and marketing hype.
- LLM scan (optional, BYOK) — if
OPENAI_API_KEYis set, a second pass with GPT-4o-mini catches subtler patterns and merges results with the rule scan.
What it returns
- patternScore (0–100) — higher = more AI-template patterns
- naturalnessLabel — human-readable tier ("Mostly natural" → "Strong AI writing signals")
- hits — list of flagged issues, each with:
id,label,severity(warn / fail)message— what's wrongexcerpt— the exact text flaggedhumanizeHint— how to rewrite it
- language, wordCount, createdAt
Quick Start
npm install
npm run build
Works out of the box with zero configuration (rule-based scan only).
Add OPENAI_API_KEY for better accuracy.
Environment variables
| Variable | Required | Default | Description |
|---|---|---|---|
OPENAI_API_KEY | No | — | Your OpenAI API key. Without it, only rule-based scan runs. |
OPENAI_BASE_URL | No | https://api.openai.com/v1 | Custom OpenAI-compatible endpoint. |
OPENAI_MODEL | No | gpt-6-luna | Model override. |
MCP Config Example
{
"mcpServers": {
"naturalmelo-mcp": {
"command": "node",
"args": ["<ABSOLUTE_PATH>/naturalmelo-mcp/dist/index.js"],
"env": {
"OPENAI_API_KEY": "sk-your-key-here"
}
}
}
}
Tool Input
{
"text": "In today's rapidly evolving digital landscape, AI has become essential...",
"mode": "general"
}
text(required) — minimum 20 charactersmode(optional) —"general"(default) or"academic"
Notes
- Rule-based scan runs locally — no network calls, no API keys.
- LLM scan uses your own OpenAI key (BYOK) — you control usage and billing.
- Academic mode skips connector-stacking and hype-flagging rules.
- Never commit
.envor API keys into git.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.