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Glama

I Ching MCP Server by RoxyAPI

by com.roxyapi

Random hexagram - I-Ching hexagram picker API

get_iching_hexagrams_random
Read-only

Receive a random I-Ching hexagram with full interpretation. Perfect for daily oracle features, meditation prompts, or exploring the Book of Changes. Returns complete hexagram data including judgment, image, interpretations for love/career/decisions, and all six changing line meanings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoResponse language (BCP 47). Supported: en, tr, de, es, hi, pt, fr, ru, zh-Hans, zh-Hant. Defaults to en. Coverage varies by domain, and a field with no translation in the requested language returns English.en
compactNoSet true for the same data in a compact shape: arrays of same-shaped objects arrive columnar as {"__cols":[names],"__rows":[[values]]}. Lossless, typically 40 to 52 percent fewer tokens.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • changedInput schema / properties / lang / description
      Previous value: -"Response language (ISO 639-1). Supported: en, tr, de, es, hi, pt, fr, ru. Defaults to en. Languages without translations yet return English."New value: +"Response language (BCP 47). Supported: en, tr, de, es, hi, pt, fr, ru, zh-Hans, zh-Hant. Defaults to en. Coverage varies by domain, and a field with no translation in the requested language returns English."
    • changedInput schema / properties / lang / enum
      Previous value: -[
-  "en",
-  "tr",
-  "de",
-  "es",
-  "hi",
-  "pt",
-  "fr",
-  "ru"
-]New value: +[
+  "en",
+  "tr",
+  "de",
+  "es",
+  "hi",
+  "pt",
+  "fr",
+  "ru",
+  "zh-Hans",
+  "zh-Hant"
+]
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {}
+]
    • changedInput schema / properties / compact / description
      Previous value: -"Set true to receive the exact same data in a token-optimized shape that is cheaper for you to read: whitespace is stripped and every array of same-shaped objects is encoded columnar as {\"__cols\":[field names],\"__rows\":[[values]]}, so each field name is sent once instead of once per row. Fully lossless (no field or value is dropped or changed) and typically 40 to 52 percent fewer tokens on large results. Prefer true whenever token or inference cost matters. Default false returns standard indented JSON."New value: +"Set true for the same data in a compact shape: arrays of same-shaped objects arrive columnar as {\"__cols\":[names],\"__rows\":[[values]]}. Lossless, typically 40 to 52 percent fewer tokens."
  3. Changed1 schema field changed
    • changedInput schema / properties / compact / description
      Previous value: -"Return the same data in a token-optimized compact shape (minified, with same-shaped arrays encoded columnar) to reduce LLM token cost. Lossless: no fields are dropped. Default false."New value: +"Set true to receive the exact same data in a token-optimized shape that is cheaper for you to read: whitespace is stripped and every array of same-shaped objects is encoded columnar as {\"__cols\":[field names],\"__rows\":[[values]]}, so each field name is sent once instead of once per row. Fully lossless (no field or value is dropped or changed) and typically 40 to 52 percent fewer tokens on large results. Prefer true whenever token or inference cost matters. Default false returns standard indented JSON."
  4. Changed1 schema field changed
    • addedInput schema / properties / compact
      Added value: +{
+  "default": false,
+  "description": "Return the same data in a token-optimized compact shape (minified, with same-shaped arrays encoded columnar) to reduce LLM token cost. Lossless: no fields are dropped. Default false.",
+  "type": "boolean"
+}
  5. First observed

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the operation read-only and non-destructive. The description adds behaviorally relevant context: the call returns a random selection, not a query result, and includes judgment, image, domain interpretations, and all six changing-line meanings. It does not fully describe data shape, but the safety profile is covered by annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences: the first states the function, the second gives use cases, and the third details return content. No repetition of schema fields, no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description usefully enumerates the returned categories. It is complete enough for an agent to invoke the tool with optional lang and compact; only exact field names and randomness details are absent, which are not required for a correct call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description adds no parameter-specific detail. That is acceptable because lang and compact are fully documented in the schema with enums, defaults, examples, and behavior. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description opens with the specific operation: 'Receive a random I-Ching hexagram with full interpretation.' It names the resource (hexagram) and the distinguishing behavior (random), and enumerates the returned interpretation domains, so it is clearly separate from lookup, number, trigram, and cast siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives concrete contexts ('daily oracle features, meditation prompts, or exploring the Book of Changes') and the word 'random' implies use when no specific hexagram is intended. It does not explicitly name sibling tools or exclusion conditions, but the intended use is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation2/5

Several tools have overlapping functionality: get_iching_hexagrams_random, post_iching_daily, get_iching_cast, and post_iching_daily_cast all return hexagram readings with interpretation, and their boundaries are subtle. The lookup variants are distinguishable, but agents could easily pick the wrong reading or casting tool.

Naming Consistency4/5

Most tools follow a clear get_iching_<resource> pattern with readable modifiers. However, the post_ prefix in two tools breaks the otherwise uniform get_ style even though all tools are fundamentally retrieval or generation endpoints.

Tool Count4/5

Nine tools is within a reasonable range for an I Ching reference and divination server, and most add a distinct access mode. The daily/random and cast/daily_cast pairs introduce slight redundancy, making the set slightly fuller than necessary.

Completeness5/5

The surface covers the core oracle workflow: casting, daily readings, lookups by number or binary pattern, listing all hexagrams, and trigram reference. There are no obvious dead ends since returned hexagrams can be re-looked-up by number.

Resources