Llm Vision Mcp
БесплатноНе проверенA TypeScript MCP server that gives text-only LLMs image understanding through StepFun vision models.
Описание
A TypeScript MCP server that gives text-only LLMs image understanding through StepFun vision models.
README
A TypeScript MCP server that gives text-only LLMs image understanding through StepFun vision models.
This is useful when the primary model, such as GLM5.2 or DeepSeek V4, does not support image input. The model can call these MCP tools, receive text or structured visual analysis, then continue reasoning with the result.
Tools
analyze_image: general image understandingextract_text_from_image: OCR for screenshots, logs, documents, code, and UI textdiagnose_error_screenshot: error screenshot and stack trace diagnosisunderstand_technical_diagram: architecture, flowchart, UML, ER, sequence, and network diagramsanalyze_data_visualization: charts, tables, dashboards, and metrics screenshotsui_to_artifact: UI screenshot to implementation notes or design specsui_diff_check: expected vs actual UI screenshot comparison
Setup
npm install
cp .env.example .env
Set STEPFUN_API_KEY in the MCP client environment. Injecting env vars through the MCP client config is usually the most explicit and reliable setup.
Required:
STEPFUN_API_KEY=your_stepfun_api_key
Optional:
# standard | step_plan
STEPFUN_API_MODE=standard
STEPFUN_BASE_URL=https://api.stepfun.com/v1
STEPFUN_VISION_MODEL=step-1o-turbo-vision
STEPFUN_DEFAULT_DETAIL=high
STEPFUN_TIMEOUT_MS=120000
Step Plan
Step Plan uses the same API key style but a different Base URL:
STEPFUN_API_MODE=step_plan
When STEPFUN_API_MODE=step_plan is set, defaults change to:
STEPFUN_BASE_URL=https://api.stepfun.com/step_plan/v1
STEPFUN_VISION_MODEL=step-3.7-flash
You can still override either value explicitly:
STEPFUN_API_MODE=step_plan
STEPFUN_BASE_URL=https://api.stepfun.com/step_plan/v1
STEPFUN_VISION_MODEL=step-3.7-flash
For backward compatibility, STEPFUN_USE_STEP_PLAN=true also enables Step Plan mode when STEPFUN_API_MODE is not set.
Run
npm run build
npm run start
Run With npx
After this package is published to npm:
npx -y llm-vision-mcp
The published package runs on Node.js and does not require Bun on the user's machine.
MCP Client Config
Example:
{
"mcpServers": {
"llm-vision-mcp": {
"command": "node",
"args": ["/Users/shaoyun/workdir/llm-vision-mcp/dist/index.js"],
"env": {
"STEPFUN_API_KEY": "your_stepfun_api_key",
"STEPFUN_API_MODE": "step_plan",
"STEPFUN_DEFAULT_DETAIL": "high"
}
}
}
}
npm package example after publishing:
{
"mcpServers": {
"llm-vision-mcp": {
"command": "npx",
"args": ["-y", "llm-vision-mcp"],
"env": {
"STEPFUN_API_KEY": "your_stepfun_api_key",
"STEPFUN_API_MODE": "step_plan",
"STEPFUN_DEFAULT_DETAIL": "high"
}
}
}
}
Image Inputs
Every single-image tool accepts:
{
"image": "/absolute/path/to/screenshot.png",
"question": "What does this error mean?",
"detail": "high"
}
The image field supports:
- local file path
file://pathhttp://orhttps://URLdata:image/...;base64,...Data URL
ui_diff_check accepts two images:
{
"expected_image": "/absolute/path/to/expected.png",
"actual_image": "/absolute/path/to/actual.png",
"question": "Focus on layout and missing buttons.",
"detail": "high"
}
Notes
- Use
detail: "high"for OCR, UI, diagrams, charts, and screenshots. - Use
detail: "low"for faster, cheaper coarse image understanding. - StepFun supports JPG/JPEG, PNG, WebP, and static GIF image inputs.
Установить Llm Vision Mcp в Claude Desktop, Claude Code, Cursor
unyly install llm-vision-mcpСтавит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.
Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh
Или настроить вручную
Выполни в терминале:
claude mcp add llm-vision-mcp -- npx -y llm-vision-mcpFAQ
Llm Vision Mcp MCP бесплатный?
Да, Llm Vision Mcp MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Llm Vision Mcp?
Нет, Llm Vision Mcp работает без API-ключей и переменных окружения.
Llm Vision Mcp — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Llm Vision Mcp в Claude Desktop, Claude Code или Cursor?
Открой Llm Vision Mcp на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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