system_stats
Check CPU, memory, disk, and network usage to monitor server health and identify performance issues.
Instructions
Get system stats (CPU, memory, disk, network)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Check CPU, memory, disk, and network usage to monitor server health and identify performance issues.
Get system stats (CPU, memory, disk, network)
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.4.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it only says 'Get system stats.' It does not state whether the call is read-only, what format the returned statistics take, whether any permissions are required, or whether the command has side effects. The minimal wording leaves most behavioral expectations implicit.
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 one short sentence that wastes no words and places the core action and object first. The parenthetical detail adds useful specificity without bloat.
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 zero-parameter system statistics read operation, the description is largely sufficient: an agent knows what to call and roughly what it will receive. It could be more complete by stating the output shape or distinguishing it from service_stats, but the low complexity of the tool reduces the need for extensive context.
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 tool has zero parameters, so the schema already exhaustively covers the input surface. The description adds useful context by listing the categories of returned data, though this is not strictly parameter-related. The baseline of 4 is appropriate for a parameterless tool.
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 states the exact action ('Get') and resource ('system stats') and enumerates the covered metrics: CPU, memory, disk, network. It is clear and self-contained, though it does not explicitly differentiate itself from the similarly named sibling tools service_stats and storage_stats.
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 that this tool is used when system-wide statistics are needed, but it gives no explicit guidance about when to prefer it over service_stats or storage_stats. It provides a general context without exclusions or alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/dray-supadev/easypanel-mcp'
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