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luma-mcp MCP Server

JochenYang/luma-mcp

Score: 59.8 ↓ 3.5% Rank #6390 MCP Server
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多模型视觉理解 MCP 服务器,为不支持图片理解的 AI 编码模型提供视觉能力:分析截图、报错、UI 与文档,可接入多家主流视觉大模型。Multi-model vision MCP server that adds image understanding to AI coding models without native vision — analyze screenshots, errors, UI and documents via major vision LLM providers.

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Overview

JochenYang/luma-mcp is a TypeScript MCP server licensed under MIT. 多模型视觉理解 MCP 服务器,为不支持图片理解的 AI 编码模型提供视觉能力:分析截图、报错、UI 与文档,可接入多家主流视觉大模型。Multi-model vision MCP server that adds image understanding to AI coding models without native vision — analyze screenshots, errors, UI and documents via major vision LLM providers. Topics: image-understanding, mcp, mcp-server, model-context-protocol, vision.

Ranked #6390 out of 24846 indexed tools.

Ecosystem

TypeScript MIT
image-understandingmcpmcp-servermodel-context-protocolvision

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 116

116 stars → growing community

Freshness 25% 2mo ago

Last commit 2mo ago → moderate activity

Issue Health 25% 86%

6/7 issues closed → responsive maintainer

Contributors 10% 1

1 contributor → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 12
Description Detailed
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Freshness high impact

Last commit was 81 days ago — a recent commit would boost your freshness score

Contributors medium impact

Single-contributor projects carry bus-factor risk — welcoming contributors boosts confidence

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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AgentRank score for JochenYang/luma-mcp
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Matched Queries

"mcp server""mcp-server"topic:mcptopic:mcp-servertopic:model-context-protocol

From the README

# Luma MCP

多模型视觉理解 MCP 服务器,为不支持原生视觉能力的 AI 助手提供统一的图片分析能力。

[English](./docs/README_EN.md) | 中文

## 特性

- **多模型支持**:GLM-4.6V、DeepSeek-OCR、Qwen3-VL-Flash、Doubao-Seed-1.6、Hunyuan-Vision
- **单工具设计**:统一通过 `image_understand` 完成图片理解,兼容旧客户端
- **面向复杂截图优化**:大图自动多裁剪、文本密集场景保真处理
- **统一预处理链路**:本地文件、远程 URL、Data URI 都进入同一套处理流程
- **适用场景完整**:代码截图、UI 截图、报错截图、文档截图、OCR
- **标准 MCP 协议**:可接入 Claude Desktop、Cline、Claude Code 等客户端
- **HTTP / Docker 部署**:局域网内多客户端共享一个实例(v1.7.0+)
- **内置重试**:降低临时网络或模型请求失败带来的影响

## 快速开始

### 前置要求

- Node.js >= 18
- 任意一个模型提供商的 API Key

### 安装

直接通过 `npx` 运行(无需本地安装):

```bash
npx -y luma-mcp
```

或从源码构建:

```bash
git clone https://github.com/JochenYang/luma-mcp.git
cd luma-mcp
npm install
npm run build
```

## 不使用 MCP?Luma Vision Skill(轻量替代)

不想安装 MCP 服务器,或你使用的 AI 客户端(如 Kimi Code)支持 skill 而不支持 MCP?可直接使用仓库内的 `vision-skill/`:

- **安装**:把 `vision-skill/` 目录复制到你所用 agent 的 skills 目录(如 `~/.agents/skills/vision-skill`)
- **激活**:发送图片时以 `/skill luma-vision` 开头,skill 会执行 `scripts/vision.js` 直连视
Read full README on GitHub →

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