Un servidor MCP que proporciona herramientas para interactuar con los buckets de AWS S3. Este servidor permite el acceso directo a las operaciones de los buckets de S3 mediante el Protocolo de Contexto de Modelo.
El servidor actualmente implementa las siguientes herramientas:
list-s3-buckets : enumera todos los buckets S3 en su cuenta de AWS
Parámetro region opcional para especificar la región de AWS
Devuelve una lista formateada de nombres de depósitos
Related MCP server: AWS S3 Control MCP Server
Python 3.13 o superior
Credenciales de AWS configuradas (consulte Configuración de credenciales de AWS )
administrador de paquetes uv
uvx install s3-toolsClonar el repositorio
Instalar usando uv:
uv pip install .Este servidor requiere credenciales de AWS para acceder a sus buckets de S3. Puede configurar las credenciales de varias maneras:
Configuración de AWS CLI (recomendada)
aws configureEsto creará/actualizará las credenciales en ~/.aws/credentials
Variables de entorno
export AWS_ACCESS_KEY_ID="your_access_key"
export AWS_SECRET_ACCESS_KEY="your_secret_key"
export AWS_DEFAULT_REGION="your_preferred_region" # optionalRol de IAM (si se ejecuta en la infraestructura de AWS)
Para obtener más información sobre las credenciales de AWS, consulte la documentación de AWS .
Agregue la configuración del servidor a su archivo de configuración de Claude Desktop:
MacOS : ~/Library/Application Support/Claude/claude_desktop_config.json
Ventanas : %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"s3-tools": {
"command": "uvx",
"args": ["s3-tools"]
}
}
}Para desarrollo/prueba, puede ejecutar el servidor directamente desde la fuente:
{
"mcpServers": {
"s3-tools": {
"command": "uv",
"args": [
"--directory",
"/path/to/s3-tools",
"run",
"s3-tools"
]
}
}
}Dependencias de sincronización:
uv syncPaquete de compilación:
uv buildPara publicar en PyPI:
uv publishNota: Necesitará credenciales de PyPI configuradas a través de:
Token: --token o UV_PUBLISH_TOKEN
O nombre de usuario/contraseña: --username / UV_PUBLISH_USERNAME y --password / UV_PUBLISH_PASSWORD
Dado que los servidores MCP se comunican a través de stdio, la depuración puede ser complicada. Recomendamos usar el Inspector MCP para el desarrollo:
npx @modelcontextprotocol/inspector uv run s3-toolsInstituto Tecnológico de Massachusetts (MIT)
¡Agradecemos sus contribuciones! No dude en enviar una solicitud de incorporación de cambios.
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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