MCP servers to handle multimodal medical data

Name: MCP servers to handle multimodal medical data
Author: Ketansuhaas

@Ketansuhaas

代码仓库

关于 MCP servers to handle multimodal medical data

Process and prepare your multimodal medical data with natural language!

#multimodal #medical #data-processing

基本信息

分类

数据与分析

运行时

python

传输方式

stdio

发布者

Ketansuhaas

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "multimodal-medical-mcp-servers": {
      "command": "uv",
      "args": [
        "init"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP servers to handle multimodal medical data?

MCP servers to handle multimodal medical data is a collection of Model Context Protocol (MCP) servers for medical data types. The currently documented server is an EEG server that enables AI assistants like Claude Desktop to interact with electroencephalography (EEG) data. It is intended for medical researchers and developers who need to integrate EEG analysis into AI workflows.

How to use MCP servers to handle multimodal medical data?

To use the EEG server, clone the repository, navigate to the eeg-server directory, initialize a Python environment with uv, and install dependencies (mcp[cli] and mne). Then configure the server in Claude Desktop by adding the appropriate command and directory paths to claude_desktop_config.json. Claude Desktop will start the server automatically when needed, or you can run it manually via the command in the configuration.

Key features of MCP servers to handle multimodal medical data

Provides an MCP server for EEG data analysis.
Uses the MNE Python library for neuroimaging data processing.
Integrates seamlessly with Claude Desktop via claude_desktop_config.json.
Relies on the uv package manager for environment setup.
Supports manual or automatic server startup.

Use cases of MCP servers to handle multimodal medical data

Enabling an AI assistant to read, analyze, or visualize EEG recordings.
Building medical decision-support tools that incorporate real-time neural data.
Automating EEG preprocessing and feature extraction through natural language commands.

FAQ from MCP servers to handle multimodal medical data

What are the prerequisites for running the server?

You need a Python environment (Anaconda recommended) and the uv package manager installed. The server also requires mcp[cli] and mne Python packages.

How do I configure the server for Claude Desktop?

Add a JSON block to claude_desktop_config.json specifying the uv executable path, the server directory, and the command run server.py. Replace placeholders with your actual username and folder paths.

Can I run the server manually?

Yes. Run the full uv command (including --directory and run server.py) from a terminal where uv is available. Be sure to replace the path placeholders.

What operating system is supported?

The README provides examples for Windows paths (e.g., C:\Users\{user}\...), indicating Windows support. Other operating systems may work but are not documented.

What data libraries does the server use?

The server uses MNE, a Python library for working with human neurophysiological data such as EEG, MEG, and iEEG.

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