get_server_load
Retrieve real-time CPU, memory, and disk usage metrics for a specified Laravel Forge server.
Instructions
Get server load metrics (CPU, memory, disk)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| serverId | Yes | The ID of the server |
Retrieve real-time CPU, memory, and disk usage metrics for a specified Laravel Forge server.
Get server load metrics (CPU, memory, disk)
| Name | Required | Description | Default |
|---|---|---|---|
| serverId | Yes | The ID of the server |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states it's a read operation for metrics, but omits important details such as whether data is real-time, authentication requirements, rate limits, or error handling for invalid serverId. This leaves the agent with incomplete understanding of side effects and constraints.
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, concise sentence with no wasted words. It front-loads the core action and resource, making it efficient for quick scanning.
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 simple tool with one parameter and no output schema, the description covers the basic purpose. However, it lacks any hint about the response format (e.g., whether metrics are returned as numbers, strings, or objects), which would help an agent parse the result. Given the low complexity, it is moderately complete.
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 100% coverage for its single parameter, providing a basic description. The tool description does not add any additional meaning beyond the schema's 'The ID of the server'. With high schema coverage, a score of 3 is baseline; no extra value is added.
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 tool retrieves server load metrics, specifying CPU, memory, and disk. This distinguishes it from sibling tools like 'get_server' (general info) and 'list_servers' (list all servers), making the purpose specific and unambiguous.
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?
No explicit guidance on when to use this tool versus alternatives. The name and description imply monitoring use, but without mentioning when to prefer 'get_server_load' over 'get_server' or 'list_servers', the agent lacks clear selection criteria.
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/OBSTechnologies/forge-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server