Install
$ agentstack add mcp-livebigorange-mcp-images ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
mcp_images
MCP 图片分析服务器 — 在 AI 工具中直接分析本地图片、剪贴板截图或 Base64 图片数据。
将图片发送至兼容 OpenAI 的 VLM API(Ollama / vLLM / DashScope / OpenAI 等),返回结构化分析结果。
快速开始
方式一:下载预编译二进制(推荐)
从 Releases 下载对应平台的二进制文件。
方式二:从源码编译
# Linux / macOS
make build # 编译当前平台
make build-all # 跨平台编译(Windows/Linux/macOS)
# Windows
./build.ps1 # 编译当前平台
./build.ps1 -Action build-all # 跨平台编译
编译产物输出到 bin/ 目录。
配置
在 AI 工具的 mcp.json 中添加(以 Ollama 为例):
{
"mcpServers": {
"mcp_images": {
"command": "/path/to/mcp_images",
"env": {
"VLM_API_BASE": "http://localhost:11434/v1/chat/completions",
"VLM_MODEL": "qwen2.5vl:7b"
}
}
}
}
更多配置示例(vLLM / DashScope / OpenAI / opencode)见 完整文档。
环境变量
| 变量 | 说明 | 默认值 | |------|------|--------| | VLM_API_BASE | VLM API 地址(必填) | — | | VLM_MODEL | 模型名(必填) | — | | VLM_API_KEY | API Key(本地模型可空) | — | | VLM_TIMEOUT | HTTP 超时秒数 | 60 | | VLM_LOG_LEVEL | 日志级别 | warn |
工具
describe_image_file— 分析本地图片文件describe_clipboard_image— 读取剪贴板截图并分析describe_base64_image— 分析 Base64 编码的图片
文档
完整文档(含多场景配置示例、使用案例):livebigorange.github.io/mcp_images
构建
# Linux / macOS
make build # 编译当前平台
make build-all # 跨平台编译
make test # 运行测试
make lint # 代码检查
# Windows
./build.ps1 # 编译当前平台
./build.ps1 -Action test # 运行测试
./build.ps1 -Action lint # 代码检查
架构
AI 工具 → stdio JSON-RPC → 图片处理 → VLM API → 结构化结果
Go 单二进制 + stdio JSON-RPC,零依赖运行。
联系
如有问题或建议,请联系 [yzn5555@163.com](mailto:yzn5555@163.com)
许可证
[MIT](./LICENSE)
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: LiveBigOrange
- Source: LiveBigOrange/mcp_images
- License: MIT
- Homepage: https://livebigorange.github.io/mcp_images/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.