El Servidor de Información del Sistema MCP es un servidor ligero y eficiente que proporciona información del sistema en tiempo real. Recupera diversos detalles del hardware y del sistema, incluyendo estadísticas de CPU, memoria, disco y GPU, lo que lo hace útil para fines de monitorización y diagnóstico.
Related MCP server: MCP System Info Server
Información del sistema
Nombre del sistema
Nombre del nodo
Versión del sistema operativo
Versión del sistema operativo
Tipo de máquina
Procesador
Información de la CPU
Nombre del procesador
Núcleos físicos
Núcleos lógicos
Información de la memoria
Memoria total
Memoria disponible
Memoria usada
Utilización de la memoria
Información del disco
Espacio total en disco
Espacio de disco usado
Espacio libre en disco
Utilización del espacio en disco
Información de la GPU
Identificación de GPU
Nombre de la GPU
Versión del controlador
Memoria total de la GPU
Memoria GPU libre
Memoria GPU usada
Carga de GPU
Temperatura de la GPU
Clonar el repositorio:
git clone https://github.com/allenbijo/mcp-sysinfo.gitAgregue el servidor MCP a su cliente:
Sobre Claude
{
"mcpServers": {
"sysinfo": {
"command": "uv",
"args": [
"--directory",
"D:\\WorksOfGreatness\\mcp-sysinfo",
"run",
"sysinfo.py"
]
}
}
}El servidor se iniciará y escuchará las solicitudes entrantes, proporcionando información del sistema en tiempo real.
Punto final | Descripción |
| Devuelve detalles del sistema |
Este proyecto está licenciado bajo la licencia MIT.
Allen Bijo - GitHub
Get the current system information. Gives system information such as System, Node name, Release, Version, Machine, Processor CPU Information such as Processor, Physical Cores, Logical Cores Memory Information such as Total Memory, Available Memory, Used Memory, Memory Utilization Disk Information such as Total Disk Space, Used Disk Space, Free Disk Space, Disk Space Utilization
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly describes the tool's read-only behavior and the types of information returned, but lacks details on performance, rate limits, or error handling. It adequately covers the core behavior without rich contextual disclosures.
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 well-structured and front-loaded with the main purpose, followed by categorized details. It is appropriately sized for the tool's complexity, though some redundancy in listing information types could be slightly condensed.
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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description provides complete context on what information is retrieved. It adequately compensates for the lack of structured fields, though it doesn't specify output format or potential errors.
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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose and output, not parameters, meeting the baseline for zero-parameter tools.
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 specific action ('Get') and resource ('current system information'), with detailed breakdowns of what information is included (System, Node name, CPU, Memory, Disk). It effectively distinguishes this tool's comprehensive scope from any hypothetical alternatives.
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 implies usage for retrieving system information, but provides no explicit guidance on when to use this tool versus alternatives (e.g., specific vs. partial system info tools). Since there are no sibling tools, this is adequate but lacks explicit context or exclusions.
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.
get_sysinfoScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'get_sysinfo' has a clear and distinct purpose of retrieving comprehensive system information, making it impossible for an agent to misselect among tools.
Since there is only one tool, it inherently follows a consistent naming pattern. The name 'get_sysinfo' uses a verb_noun format that is clear and predictable, and there are no other tools to compare it against for inconsistency.
A single tool is too few for a server named 'MCP System Info Server', which suggests a broader scope for system information retrieval. While 'get_sysinfo' provides comprehensive data, the lack of additional tools (e.g., for specific components like CPU, memory, or disk details) makes the set feel thin and underdeveloped for the domain.
The tool 'get_sysinfo' covers a wide range of system information in one call, but the server's purpose implies potential for more granular operations. There are significant gaps, such as no tools for querying specific system metrics separately (e.g., get_cpu_info, get_memory_usage) or performing actions like monitoring changes, which limits agent flexibility and could lead to inefficiencies.
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