Check server version, uptime, and per-dataset request statistics to confirm you are connected to the intended endpoint before running queries.
Version, uptime and per-dataset request statistics.
Worth a call at the start of a session to confirm you are talking to the server you think you are -- a wrong endpoint that happens to answer is otherwise hard to spot.
| Name | Required | Description | Default |
|---|---|---|---|
| dataset | No | Limit the statistics to one dataset. |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It implies a non-mutating read via its metrics-flavored content and adds a genuinely useful behavioral frame: detecting a wrong endpoint that still answers. It does not state read-only status outright, nor permissions, rate limits, or caching behavior.
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?
Two sentences, zero filler, and the payoff (what it returns) is front-loaded ahead of the rationale for calling it. Every sentence earns its place.
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?
No output schema or annotations, but the description enumerates the returned fields (version, uptime, per-dataset stats) well enough for an agent to know what to expect. The only real omission is any contrast with the similarly named dataset_stats sibling.
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% and the single optional 'dataset' parameter is fully documented in the schema as limiting statistics to one dataset. The description adds no syntax or format details beyond that, so the baseline 3 for schema-covered params applies.
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?
Names a specific verb-less but concrete resource set: version, uptime, and per-dataset request statistics. An agent knows exactly what comes back. However, it never distinguishes itself from the sibling dataset_stats, which sounds like it could return overlapping statistics, so sibling differentiation is missing.
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?
Explicitly states when to call it ('at the start of a session') and why (confirming the endpoint identity). No exclusions or named alternatives are given, so it stops short of the 5-level when-not/alternatives guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.