提供与 AWS S3 bucket 交互工具的 MCP 服务器。该服务器支持通过模型上下文协议 (MCP) 直接访问 S3 bucket 操作。
该服务器目前实现了以下工具：
list-s3-buckets ：列出您的 AWS 账户中的所有 S3 存储桶
可选region参数，用于指定 AWS 区域
返回存储桶名称的格式化列表
Related MCP server: AWS S3 Control MCP Server
uvx install s3-tools克隆存储库
使用 uv 安装：
uv pip install .此服务器需要 AWS 凭证才能访问您的 S3 存储桶。您可以通过多种方式配置凭证：
AWS CLI 配置（推荐）
aws configure这将在~/.aws/credentials中创建/更新凭证
环境变量
export AWS_ACCESS_KEY_ID="your_access_key"
export AWS_SECRET_ACCESS_KEY="your_secret_key"
export AWS_DEFAULT_REGION="your_preferred_region" # optionalIAM 角色（如果在 AWS 基础设施上运行）
有关 AWS 凭证的更多信息，请参阅AWS 文档。
将服务器配置添加到您的 Claude Desktop 配置文件：
MacOS ： ~/Library/Application Support/Claude/claude_desktop_config.json
Windows ： %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"s3-tools": {
"command": "uvx",
"args": ["s3-tools"]
}
}
}对于开发/测试，您可以直接从源代码运行服务器：
{
"mcpServers": {
"s3-tools": {
"command": "uv",
"args": [
"--directory",
"/path/to/s3-tools",
"run",
"s3-tools"
]
}
}
}同步依赖项：
uv sync构建包：
uv build要发布到 PyPI：
uv publish注意：您需要通过以下方式配置 PyPI 凭据：
令牌： --token或UV_PUBLISH_TOKEN
或用户名/密码： --username / UV_PUBLISH_USERNAME和--password / UV_PUBLISH_PASSWORD
由于 MCP 服务器通过 stdio 进行通信，调试起来可能比较困难。我们建议使用MCP Inspector进行开发：
npx @modelcontextprotocol/inspector uv run s3-tools麻省理工学院
欢迎贡献代码！欢迎提交 Pull 请求。
List all S3 buckets in your AWS account
| Name | Required | Description | Default |
|---|---|---|---|
| region | No | AWS region (optional, defaults to configured region) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'all S3 buckets' which implies completeness, but doesn't address permissions needed, rate limits, pagination, error conditions, or what the output looks like. For a tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and minimal behavioral disclosure, the description is incomplete. It should address authentication requirements, output format, and potential limitations given this is an AWS operation that could have permission constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the single optional 'region' parameter. The description doesn't add any parameter-specific information beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('all S3 buckets in your AWS account'), providing a specific verb+resource combination. It doesn't need to distinguish from siblings since none exist, so it earns a 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It simply states what the tool does without any usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
list-s3-bucketsScored across 1 tool
With only one tool, there is no possibility for ambiguity or overlap between tools, as there are no other tools to compare it to. The tool's purpose is clearly defined and distinct by default.
Since there is only one tool, naming consistency is inherently perfect with no deviations or mixed conventions to evaluate. The tool name 'list-s3-buckets' follows a clear verb_noun pattern.
A single tool for an S3 server is too few for the apparent scope, as S3 involves operations like uploading, downloading, deleting objects, and managing buckets beyond listing. This minimal set will likely cause agent failures due to significant functional gaps.
The tool surface is severely incomplete for an S3 domain, covering only bucket listing. There are obvious gaps for core operations such as creating/deleting buckets, managing objects (upload, get, delete), and other essential S3 functionalities, making it inadequate for typical use cases.
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