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Dream Interpretation MCP Server by RoxyAPI

Random dream symbols - Dream symbol discovery API

get_dreams_symbols_random
Read-only

Discover random dream symbols and their interpretations for daily dream insights and exploration. Each request returns different symbols from the 2,200+ dream meaning database, perfect for dream of the day features, dream journaling prompts, meditation on subconscious themes, or exploring what different dreams mean. Get one or multiple random dream interpretations with full psychological meanings.

Input Schema

NameRequiredDescriptionDefault
countNoNumber of random symbols to return (1-10). Default: 1.
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.

Output Schema

NameRequiredDescriptionDefault
symbolsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "symbols": {
      +      "items": {
      +        "properties": {
      +          "id": {
      +            "type": "string"
      +          },
      +          "letter": {
      +            "type": "string"
      +          },
      +          "meaning": {
      +            "type": "string"
      +          },
      +          "name": {
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "id",
      +          "name",
      +          "letter",
      +          "meaning"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "required": [
      +    "symbols"
      +  ],
      +  "type": "object"
      +}
  2. Changed1 schema field changed
    • changedInput schema / properties / count / type
      Previous value: -"number"New value: +"integer"
  3. 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."
  4. 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."
  5. 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"
      +}
  6. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavior the annotations cannot: each call returns different results (non-deterministic), drawn from a 2,200+ entry database, and can return one or many symbols. It stops short of describing pagination or response shape, but the output schema handles that.

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

Conciseness3/5

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

The purpose is front-loaded correctly, but the middle sentence pads with four promotional use cases ('dream of the day features, dream journaling prompts, meditation on subconscious themes, exploring what different dreams mean') that largely restate one another. It is serviceable but not tight.

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?

For a zero-required-parameter read tool with an output schema, the description covers what is returned, the randomness behavior, and the dataset scale. Nothing essential to invocation is missing; only the sibling relationship is left unstated.

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%, with both 'count' and 'compact' fully documented in the schema itself, so the baseline is 3. The description only echoes 'one or multiple' interpretations and adds no syntax or format detail beyond what the schema provides.

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

Purpose4/5

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

The description states a specific verb and resource ('Discover random dream symbols and their interpretations') and the word 'random' implicitly separates it from the lookup-style siblings like get_dreams_symbols_id and get_dreams_symbols_letters. It never names an alternative, so an agent must infer the boundary rather than being told it.

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

Usage Guidelines3/5

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

It lists concrete use cases ('dream of the day features, dream journaling prompts, meditation'), which implies when the tool fits, but gives no explicit when-not guidance and never contrasts itself with the sibling symbol tools. Usage is suggested rather than routed.

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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