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Mcp_server_s3_download_files

@ENGRZULQARNAIN

代码仓库

关于 Mcp_server_s3_download_files

This repository provides an implementation of a Model Context Protocol (MCP) server for AWS S3, enabling AI models, particularly Large Language Models (LLMs), to securely interact with S3 buckets. The server offers a standardized interface to list S3 buckets, list objects within

#ai#aws-s3#large-language-models#agentic-workflow#agentic-ai#agentic-tool-platform#mcp-server

基本信息

分类

文件与存储

运行时

python

传输方式

stdio

发布者

ENGRZULQARNAIN

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp_server_s3_download_files": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

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_server_s3_download_files?

Mcp_server_s3_download_files is an implementation of the Model Context Protocol (MCP) server for AWS S3. It provides a standardized interface enabling AI models, particularly large language models (LLMs), to securely list S3 buckets, list objects within buckets, and download file contents. The server is designed for developers integrating AI applications with AWS S3 for data retrieval and management.

How to use Mcp_server_s3_download_files?

Install the server via PyPI using uv add mcp-s3-server (recommended) or pip install mcp-s3-server. For a development install, clone the repository and run uv sync or pip install -e .. Configure AWS credentials using the credentials file, environment variables, or IAM roles. Start the server by running the mcp-s3-server command, then integrate with an AI model via the MCP interface.

Key features of Mcp_server_s3_download_files

  • List S3 buckets in an AWS account.
  • List objects within a specified bucket.
  • Download contents of specific objects (e.g., files).
  • Secure, standardized interface for AI models.
  • Part of the Model Context Protocol ecosystem.

Use cases of Mcp_server_s3_download_files

  • Access and analyze data stored in S3 for AI-driven applications.
  • Retrieve specific files (e.g., PDFs) for processing by AI models.
  • Automate S3 bucket management tasks via natural language queries.
  • Support AI development requiring external data sources.

FAQ from Mcp_server_s3_download_files

What are the prerequisites for using this server?

You need Python 3.10 or higher, configured AWS credentials (Access Key ID, Secret Access Key, and Region), the uv package manager (recommended) or pip, and familiarity with the Model Context Protocol.

How do I install the server?

The recommended method is to install from PyPI using uv add mcp-s3-server or pip install mcp-s3-server. For development, clone the repository and run uv sync or pip install -e . in the project directory.

How do I configure AWS credentials?

You can configure credentials using the AWS credentials file (~/.aws/credentials), environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION), or IAM roles (for EC2 instances).

What are the limitations of this implementation?

Some versions may support only specific file types (e.g., PDFs), have limits on the number of retrieved objects (e.g., up to 1000 objects), or require configuration for the maximum number of buckets returned.

How do I start the server after installation?

After configuring AWS credentials, run the command mcp-s3-server in your terminal. The server will start and be ready to integrate with an AI model via the MCP interface.

评论

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