SiliconFlow-Vision-MCP
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., "@SiliconFlow-Vision-MCPAnalyze this UI mockup screenshot and generate the code for it"
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.
SiliconFlow-Vision-MCP
基于 SiliconFlow 多模态视觉 API(OpenAI 兼容格式)的 MCP 服务器,提供 8 个视觉工具 + 模型列表查询。
环境要求
bun ≥ 1.0
SiliconFlow API Key(https://cloud.siliconflow.cn/ 获取)
Related MCP server: Vison-MCP
安装与启动
bun install # 安装依赖(已含 @modelcontextprotocol/sdk)
bun run src/index.js # 启动 MCP server(stdio)配置 API Key
默认从环境变量 SILICONFLOW_API_KEY 读取。
Windows(PowerShell)
临时设置(仅当前会话):
$env:SILICONFLOW_API_KEY = "sk-你的Key"永久设置(用户级环境变量):
setx SILICONFLOW_API_KEY "sk-你的Key"Linux / macOS
临时设置:
export SILICONFLOW_API_KEY="sk-你的Key"永久设置(写入 ~/.bashrc 或 ~/.zshrc):
echo 'export SILICONFLOW_API_KEY="sk-你的Key"' >> ~/.bashrc
source ~/.bashrc自定义环境变量名
如需让 server 从其他变量读取 Key,设置 SILICONFLOW_API_KEY_NAME 指向目标变量:
Windows:
$env:SILICONFLOW_API_KEY_NAME = "MY_KEY"Linux/macOS:
export SILICONFLOW_API_KEY_NAME=MY_KEY
也可在 MCP 客户端配置中通过 env 注入(见下方示例)。
可选环境变量:
变量 | 默认值 | 说明 |
| - | API Key(必填) |
|
| 指定从哪个环境变量读 Key |
|
| 兼容服务地址 |
工具列表
工具 | 说明 |
| UI 截图 → 代码 / 提示词 / 设计规范 / 描述 |
| 截图 OCR 文字提取(代码、终端、文档) |
| 错误弹窗/堆栈/日志截图 → 定位与修复建议 |
| 架构图/流程图/UML/ER 图结构化解读 |
| 仪表盘/图表 → 趋势、异常、业务要点 |
| 两张 UI 截图对比,识别视觉差异 |
| 通用图像理解(自由提问) |
| 视频场景解析(本地 ≤8MB,MP4/MOV/M4V) |
| 拉取远端可用多模态模型列表 |
所有视觉工具均支持 model 参数覆盖默认模型;默认模型 Qwen/Qwen3-VL-8B-Instruct(速度快、成本低;对质量要求高时可显式指定 Qwen/Qwen3-VL-32B-Instruct)。
内置模型能力(2026-08-04 对 SiliconFlow API 实测,发送最小图片/音频/视频探测,比文档更可靠;实测脚本见 scripts/probe-multimodal.mjs):
模型 | 图片 | 音频 | 视频 |
Qwen/Qwen3-VL-8B-Instruct(默认) | ✅ | — | ✅ |
Qwen/Qwen3-VL-32B-Instruct | ✅ | — | ✅ |
Qwen/Qwen3-Omni-30B-A3B-Instruct | ✅ | ✅ | ✅ |
zai-org/GLM-4.5V | ✅ | — | — |
deepseek-ai/DeepSeek-OCR | ✅ | — | — |
PaddlePaddle/PaddleOCR-VL-1.5 | ✅ | — | — |
注意:视频分析只能使用支持视频的模型(Qwen3-VL / Qwen3-Omni 系列);stepfun-ai/Step-3.5-Flash 经实测不是多模态模型,已从内置列表移除。
媒体输入支持三种形式:
本地文件路径(server 读取后转 base64,隐私:日志不记录路径与内容)
http(s)://URL(透传给远端)data:URI(base64)
大小限制:图片 20MB,视频 8MB(本地文件)。
注册到 Codex
在 ~/.codex/config.toml 中追加(将 <项目路径> 替换为实际路径):
[mcp_servers.siliconflow-vision-mcp]
command = "bun"
args = ["run", "<项目路径>/src/index.js"]
[mcp_servers.siliconflow-vision-mcp.env]
SILICONFLOW_API_KEY = "{env:SILICONFLOW_API_KEY}"路径写法:
Windows:
C:\Users\你的用户名\siliconflow-vision-mcp\src\index.js(TOML 中用单引号包裹,反斜杠无需转义)Linux/macOS:
/home/你的用户名/siliconflow-vision-mcp/src/index.js
{env:...} 为 Codex 环境变量引用语法;也可以直接写入明文(不推荐)。
注册到其他 MCP 客户端(示例)
opencode ~/.config/opencode/opencode.jsonc:
{
"mcp": {
"siliconflow-vision-mcp": {
"type": "local",
"command": ["bun", "run", "<项目路径>/src/index.js"],
"enabled": true,
"environment": {
"SILICONFLOW_API_KEY": "{env:SILICONFLOW_API_KEY}"
}
}
}
}验证
# 协议与工具注册检查(无需 API Key)
bun run scripts/verify.mjs
# 真实 API 调用检查(需要 SILICONFLOW_API_KEY)
bun run scripts/verify-live.mjsThis server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseAqualityAmaintenanceMulti-model vision understanding MCP server that provides unified image analysis for AI assistants without native vision, supporting models like GLM-4.6V, DeepSeek-OCR, Qwen3-VL-Flash, and more.Last updated11,29693MIT
- AlicenseAqualityBmaintenanceMCP server for vision AI — screenshots to code, OCR, error diagnosis, and image analysis via OpenAI-compatible APIs.Last updated82MIT
- FlicenseAqualityBmaintenanceOpenAI-compatible vision MCP server with 14 provider presets that enables MCP clients to analyze images, including screenshots, text, and UI mockups, via a single analyze_image tool.Last updated2
- Alicense-qualityAmaintenanceA remote MCP server providing 7 vision tools (UI-to-code, OCR, error diagnosis, etc.) via an Anthropic-compatible model API, supporting multiple MCP clients through Streamable HTTP.Last updated34MIT
Related MCP Connectors
MCP server for Google Veo AI video generation
MCP server for ByteDance Seedream AI image generation
MCP server for Wan AI video generation
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/klx1204/SiliconFlow-Vision-MCP'
If you have feedback or need assistance with the MCP directory API, please join our Discord server