# FerroLaser Parts Knowledge MCP Server

> FerroLaser Parts Knowledge MCP Server — jinweihan-ai-ferrolaser-parts-mcp. Use this tool when you need to access comprehensive information about fiber laser machine parts and components to answer technical questions or resolve issues related to specifications, alarm codes, wiring, and consumables. It provides structured knowledge from official manuals, enabling AI assistants to offer accurate and reliable support. Ideal for troubleshooting, maintenance, and operational inquiries, this tool streamlines the process of finding critical information about fiber laser machines.

Canonical page: https://skillsregistry.net/skills/jinweihan-ai-ferrolaser-parts-mcp  
JSON: https://api.skillsregistry.net/v1/skills/jinweihan-ai-ferrolaser-parts-mcp

## Description

Provides structured knowledge about fiber laser machine parts and components, enabling AI assistants to answer questions about specifications, alarm codes, wiring, and consumables from official manuals.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ebbnapc0dd)
- **Repository:** <https://github.com/jinweihan-ai/ferrolaser-parts-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "jinweihan-ai-ferrolaser-parts-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jinweihan-ai-ferrolaser-parts-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jinweihan-ai-ferrolaser-parts-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt