Coal Grade Quality MCP Server
Click on "Install 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., "@Coal Grade Quality MCP ServerAnalyze this coal ore image and give me the quality grade."
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.
Coal Grade Quality MCP Server
MCP (Model Context Protocol) server that exposes a trained coal ore quality classifier as an LLM-accessible tool — allowing Claude and other MCP-compatible clients to classify coal images into quality grades .
What This Does
Upload a coal ore image → get a quality grade back through natural language.
Claude interprets the result, explains its reasoning, and flags any uncertainty
Related MCP server: readpic MCP Server
Grades
Grade | Quality |
grade_a | Highest quality — high carbon content |
grade_b | Medium quality — moderate carbon content |
grade_c | Lower quality — visible impurities |
reject | Not suitable for industrial use |
How It Works
Coal image (base64) ↓ Non-Local Means Denoising ↓ Color Histogram Extraction (96 features) ↓ StandardScaler normalization ↓ Logistic Regression prediction ↓ Grade + Confidence
MCP PRIMITIVES
Primitive | Name | Purpose | Invocation |
Tool |
| Runs the ML model on a coal image → grade + confidence | LLM-controlled |
Resource |
| Grade definitions as reference context | Host-controlled |
Prompt |
| Structured reasoning template for deep analysis | User-controlled |
Connect Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"coal-grade-server": {
"command": "path/to/venv/Scripts/python.exe",
"args": ["path/to/server.py"]
}
}
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