io.github.jkawamoto/mcp-florence2

平台与服务

by jkawamoto

An MCP server for processing images using Florence-2

什么是 io.github.jkawamoto/mcp-florence2

An MCP server for processing images using Florence-2

README

Florence-2 MCP Server

uv Python Application pre-commit GitHub License

MseeP.ai Security Assessment Badge

An MCP server for processing images using Florence-2.

You can process images or PDF files stored on a local or web server to extract text using OCR (Optical Character Recognition) or generate descriptive captions summarizing the content of the images.

Installation

Claude

Download the latest MCP bundle mcp-florence2.mcpb from the Releases page, then open the downloaded .mcpb file or drag it into the Claude Desktop's Settings window.

<details> <summary>Manually configuration</summary>

You can also manually configure this server for Claude Desktop. Edit the claude_desktop_config.json file by adding the following entry under mcpServers:

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

After editing, restart the application.

</details>

For more information, see: Connect to local MCP servers - Model Context Protocol.

goose

Open this link

code
goose://extension?cmd=uvx&arg=--from&arg=git%2Bhttps%3A%2F%2Fgithub.com%2Fjkawamoto%2Fmcp-florence2&arg=mcp-florence2&id=florence2&name=Florence-2&description=An%20MCP%20server%20for%20processing%20images%20using%20Florence-2

to launch the installer, then click "Yes" to confirm the installation.

<details> <summary>Manually configuration</summary>

You can also directly edit the config file (~/.config/goose/config.yaml) to include the following entry:

yaml
extensions:
  florence2:
    name: Florence-2
    cmd: uvx
    args: [ --from, git+https://github.com/jkawamoto/mcp-florence2, mcp-florence2 ]
    enabled: true
    type: stdio
</details>

For more details on configuring MCP servers in Goose, refer to the documentation: Using Extensions | goose.

LM Studio

To configure this server for LM Studio, click the button below.

Add MCP Server florence-2 to LM Studio

Tools

ocr

Process an image file or URL using OCR to extract text.

Arguments:

  • src: A file path or URL to the image file that needs to be processed.

caption

Processes an image file and generates captions for the image.

Arguments:

  • src: A file path or URL to the image file that needs to be processed.

process

Processes an image file with a custom prompt using the Florence-2 model.

Arguments:

  • src: A file path or URL to the image file that needs to be processed.
  • prompt: A custom prompt for the Florence-2 model.

License

This application is licensed under the MIT License. See the LICENSE file for more details.

常见问题

io.github.jkawamoto/mcp-florence2 是什么?

An MCP server for processing images using Florence-2

相关 Skills

MCP构建

by anthropics

Universal
热门

聚焦高质量 MCP Server 开发,覆盖协议研究、工具设计、错误处理与传输选型,适合用 FastMCP 或 MCP SDK 对接外部 API、封装服务能力。

想让 LLM 稳定调用外部 API,就用 MCP构建:从 Python 到 Node 都有成熟指引,帮你更快做出高质量 MCP 服务器。

平台与服务
未扫描176.4k

Slack动图

by anthropics

Universal
热门

面向Slack的动图制作Skill,内置emoji/消息GIF的尺寸、帧率和色彩约束、校验与优化流程,适合把创意或上传图片快速做成可直接发送的Slack动画。

帮你快速做出适配 Slack 的动图,内置约束规则和校验工具,少踩上传与播放坑,做表情包和演示都更省心。

平台与服务
未扫描176.4k

接口测试套件

by alirezarezvani

Universal
热门

扫描 Next.js、Express、FastAPI、Django REST 的 API 路由,自动生成覆盖鉴权、参数校验、错误码、分页、上传与限流场景的 Vitest 或 Pytest 测试套件。

帮你把API与集成测试自动化跑顺,减少回归漏测;能力全面,尤其适合复杂接口场景的QA团队。

平台与服务
未扫描26.0k

相关 MCP Server

Slack 消息

编辑精选

by Anthropic

热门

Slack 是让 AI 助手直接读写你的 Slack 频道和消息的 MCP 服务器。

这个服务器解决了团队协作中需要 AI 实时获取 Slack 信息的痛点,特别适合开发团队让 Claude 帮忙汇总频道讨论或发送通知。不过,它目前只是参考实现,文档有限,不建议在生产环境直接使用——更适合开发者学习 MCP 如何集成第三方服务。

平台与服务
89.7k

by netdata

热门

io.github.netdata/mcp-server 是让 AI 助手实时监控服务器指标和日志的 MCP 服务器。

这个工具解决了运维人员需要手动检查系统状态的痛点,最适合 DevOps 团队让 Claude 自动分析性能数据。不过,它依赖 NetData 的现有部署,如果你没用过这个监控平台,得先花时间配置。

平台与服务
80.0k

by d4vinci

热门

Scrapling MCP Server 是专为现代网页设计的智能爬虫工具,支持绕过 Cloudflare 等反爬机制。

这个工具解决了爬取动态网页和反爬网站时的头疼问题,特别适合需要批量采集电商价格或新闻数据的开发者。不过,它依赖外部浏览器引擎,资源消耗较大,不适合轻量级任务。

平台与服务
72.9k

评论