server_timeReturn the Kraken exchange server time as Unix timestamp and RFC 1123 string. Use to synchronize request timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| rfc1123 | No | RFC 1123 formatted time | |
| unixtime | No | Unix timestamp |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {}
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "rfc1123": {
+ "description": "RFC 1123 formatted time",
+ "type": "string"
+ },
+ "unixtime": {
+ "description": "Unix timestamp",
+ "type": "integer"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds useful context by specifying the return formats, which helps the agent understand what to expect. It doesn't mention rate limits or authentication, but these are not critical for a simple server-time endpoint, and the annotations cover the safety profile.
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 two sentences with no waste. It front-loads the core purpose and then adds the use case. Every word earns its place, and it is appropriately sized for the tool's simplicity.
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 (no parameters, no nested objects), an output schema is present to describe return values, and annotations cover behavioral traits, the description is complete. It provides the essential purpose and usage guidance without superfluous detail.
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 there is nothing to document. The baseline for no parameters is 4, indicating that the description adequately handles the situation by not pretending to explain non-existent inputs. The schema coverage is 100% (trivially), so no compensation is needed.
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's function: returning the Kraken exchange server time in two specific formats (Unix timestamp and RFC 1123 string). It uses a specific verb ('Return') and a distinct resource, making it easy to differentiate from sibling tools like 'ticker' or 'trades'.
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 explicitly says 'Use to synchronize request timestamps,' providing a clear use case. While it doesn't mention alternatives, the tool is uniquely positioned for time synchronization, and the guidance is direct and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes, such as the four ask_pipeworx variants and several Polymarket analysis tools. While descriptions are detailed, the distinctions are nuanced, and an agent may struggle to select the correct tool without careful reading.
Tool names mix styles: Kraken tools are short nouns (ticker, depth), while Pipeworx tools use various patterns (verb_noun, noun_noun). No single convention dominates, but names are generally readable and descriptive.
40 tools is high, combining two distinct domains. Many tools serve overlapping purposes, making the set feel bloated. A more focused server or consolidation of similar tools would improve scope.
The Pipeworx data tools cover a broad range of retrieval and analysis, including prediction markets, memory, and subscriptions. However, the Kraken tools lack trading functionality, and there are redundant tools that could be merged.