What model does the server use?
It uses Microsoft’s Florence‑2 (Florence‑2‑large) hosted on Hugging Face.
@jkawamoto
基本信息
An MCP server for processing images using Florence-2
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"florence-2": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/jkawamoto/mcp-florence2",
"mcp-florence2"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
An MCP (Model Context Protocol) server that processes images and PDF files using Microsoft’s Florence-2 model. It provides OCR to extract text and generates descriptive captions for images. Designed for developers and AI assistants (Claude, Goose, LM Studio) that need vision-based language model capabilities.
Install via the pre-built .mcpb bundle (for Claude Desktop) or by adding manual configuration entries to the claude_desktop_config.json, Goose config.yaml, or LM Studio MCP settings. All configurations use uvx to run the server from the Git repository. The server exposes two tools: ocr (extract text) and caption (generate captions), both accepting a src argument (file path or URL).
uvx for reproducible Python environmentsIt uses Microsoft’s Florence‑2 (Florence‑2‑large) hosted on Hugging Face.
For Claude Desktop, download the `.mcpb` bundle from the Releases page and open it. For Goose, use the provided deeplink or edit `~/.config/goose/config.yaml`. For LM Studio, click the “Add MCP Server” button in the README.
Yes. The OCR tool can extract text from PDFs as well as images.
The server runs via `uvx`, so you need `uv` (or a Python environment with `uvx`). No additional Python package installation is required – `uvx` automatically fetches the dependencies.
All processing is performed locally on the user’s machine. The server reads image/PDF files from the local filesystem or fetches them from a provided URL.

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