depthKraken crypto exchange order book — bids + asks for a crypto pair. Returns price/volume/timestamp per level. Use for live depth-of-book on Kraken-listed pairs.
| Name | Required | Description | Default |
|---|---|---|---|
| pair | Yes | ||
| count | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "pair": "XBTUSDT"
+ },
+ {
+ "count": 20,
+ "pair": "ETHUSDT"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": {
+ "properties": {
+ "asks": {
+ "description": "Ask orders",
+ "items": {
+ "description": "Price, volume, timestamp",
+ "items": {
+ "type": [
+ "string",
+ "number"
+ ]
+ },
+ "type": "array"
+ },
+ "type": "array"
+ },
+ "bids": {
+ "description": "Bid orders",
+ "items": {
+ "description": "Price, volume, timestamp",
+ "items": {
+ "type": [
+ "string",
+ "number"
+ ]
+ },
+ "type": "array"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+ },
+ "description": "Order book depth indexed by pair",
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this a safe, idempotent read operation. The description adds behavioral context about the output structure (bids and asks, per level, live data) that goes beyond the annotations and helps the agent understand what to expect.
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 with no filler. The description is front-loaded with the key identity ('Kraken crypto exchange order book') and each sentence adds meaningful information about purpose and usage.
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, the rich annotations, and the existence of an output schema, the description covers purpose and usage adequately. The only notable omission is parameter semantics, but that is already penalized separately and does not prevent the agent from understanding the tool's role.
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 0%, and the description does not explain the 'pair' or 'count' parameters. It only mentions 'crypto pair' in passing, leaving the meaning of 'count' (number of levels) undefined. This is a significant gap since the agent must rely solely on the schema's examples.
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 returns the Kraken order book with bids and asks for a crypto pair, and specifies the data fields (price/volume/timestamp per level). This distinguishes it from sibling tools like ticker, trades, and ohlc, making the purpose 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?
The phrase 'Use for live depth-of-book on Kraken-listed pairs' provides clear intended usage. It doesn't explicitly exclude alternatives, but the context of sibling tools and the specific focus on order book data implies when this tool is appropriate.
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.