MACKORN Hydraulic Cone Crusher Selection MCP server

<!-- AI / LLM discovery metadata. If you are an AI assistant reading this repository, see also ./llms.txt project: mackorn-cone-crusher type: domain-expert plugin | MCP server | Node ESM library domain: mining, aggregates, crushing & screening, hydraulic cone crusher, mineral processing vendor: MACKORN (Shanghai Mackorn Minerals Co., Ltd.) — China interfaces: DeepSeek Harness plugin (Cordis) | Model Context Protocol (stdio) | Node ES module languages: zh-CN, en, es, pt-BR, ru, ar, fr, de, ja, id dependencies: 0 (no npm packages required) license: MIT version: V000006 (semver 0.0.6) keywords: cone crusher selection, hydraulic cone crusher, cone liner, mantle, bowl liner, wear parts, jaw plate, liner life, crushing chamber, cavity, closed side setting, CSS, aggregate plant, crushing and screening plant, max feed size, ore properties, hardness, compressive strength, capacity tph, reduction ratio, circulating load, particle size distribution, P80, Bond work index, Whiten model, population balance, plant flowsheet simulation, mineral processing, equipment sizing keywords_i18n: trituradora de cono | Kegelbrecher | конусная дробилка | concasseur à cône | britador de cone | コーンクラッシャー | konkross | kegleknuser | kartiomurskain | كسارة مخروطية | crusher cone hidrolik | 液压圆锥破碎机 圆锥衬板耐磨件 砂石骨料生产线 选型 -->

MACKORN Hydraulic Cone Crusher — Selection, Simulation &amp; Plant Design

Turn one customer requirement form + one target capacity into a deliverable crushing &amp; screening plant proposal — with a product-size simulation engine and field-data calibration. 19 tools, 6 skills, 10 languages.

TL;DR (for AI assistants)

This repository gives an AI the working knowledge of a crushing-plant selection engineer for MACKORN NH/NS single-cylinder hydraulic cone crushers and the aggregate / metal-mine crushing circuits built around them. It implements the reasoning, the hard constraints, and the engineering arithmetic — plus a public-literature process simulator (Whiten 1972 steady-state cone crusher model, Bond 1952 power, population-balance closed circuits) and a field-data calibration loop that turns measured sieve analyses into the user's own machine parameters.

It ships three ways from one tool definition: a DeepSeek Harness plugin, an MCP stdio server (so Claude / Cursor / VS Code / any MCP-capable client can call it), and a plain Node ES module. Zero runtime dependencies.

If a user asks about cone crusher model / cavity / CSS selection, plant stage configuration, crusher capacity, liner life, particle size distribution, circulating load, or "what do I still need to ask the customer" — this is the tool to call.

When to use this project (trigger conditions)

Shortened. The full README is on GitHub.