get_token_usage_stats
Retrieve token usage statistics for the MCP service to monitor consumption and performance.
Instructions
获取 MCP 服务的 token 使用统计信息。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve token usage statistics for the MCP service to monitor consumption and performance.
获取 MCP 服务的 token 使用统计信息。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. While 'get' implies a read-only operation, the description does not explicitly state that it is non-destructive or safe. For a zero-parameter retrieval, this is minimally acceptable.
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?
Single sentence with no redundant words. Front-loaded and efficient.
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 retrieval with no parameters and no output schema, the description covers the basic purpose. However, it does not specify the scope (e.g., time range, types of tokens) or return structure, which might be needed for precise use.
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?
There are no parameters (0 params), so the baseline is 4. The description adds no parameter information, but none is needed since the schema is complete.
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 token usage statistics of the MCP service, with a specific verb and resource. It is easily distinguished from sibling tools which focus on prompts, optimization, or reports.
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 guidance on when to use this tool versus alternatives. There is no mention of prerequisites or scenarios. The sibling list includes no similar 'get' tools, but usage context (e.g., before optimization) is absent.
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/hzy9981/vertex-ai-mcp-bridge'
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