Florence-2 MCP Server

Name: Florence-2 MCP Server
Author: jkawamoto

@jkawamoto

Repository

About Florence-2 MCP Server

An MCP server for processing images using Florence-2

#python #florence-2 #mcp-server

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "florence-2": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/jkawamoto/mcp-florence2",
        "mcp-florence2"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Florence-2 MCP Server?

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.

How to use Florence-2 MCP Server?

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).

Key features of Florence-2 MCP Server

OCR for text extraction from images and PDFs
Image caption generation
Supports local file paths and remote URLs as input
Easy one‑click installs for Claude, Goose, and LM Studio
Runs via uvx for reproducible Python environments

Use cases of Florence-2 MCP Server

Extracting printed or handwritten text from scanned documents and photos
Generating alt‑text or summaries for images in a document workflow
Automating captioning of product images in an e‑commerce pipeline
Enabling voice‑assistant image analysis (e.g., reading a whiteboard photo aloud)
Integrating vision capabilities into LLM‑based AI agents without cloud dependencies

FAQ from Florence-2 MCP Server

What model does the server use?

It uses Microsoft’s Florence‑2 (Florence‑2‑large) hosted on Hugging Face.

How do I install it?

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.

Can it process PDF files?

Yes. The OCR tool can extract text from PDFs as well as images.

What are the runtime requirements?

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.

Where does data processing happen?

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.

Comments

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