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 2,000+ 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

TableJSON Schema

Name	Required	Description	Default
`count`	No	Number of random symbols to return (1-10). Default: 1.
`compact`	No	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.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`symbols`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026

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"
+}

Changed1 schema field changedSep 19, 2026
- changedInput schema / properties / count / type
```
Previous value: -"number"New value: +"integer"
```

Changed2 schema fields changedAug 17, 2026

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."

Changed1 schema field changedJul 22, 2026

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."

Changed1 schema field changedJul 22, 2026

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"
+}

First observedJul 8, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already signal readOnly and non-destructive, so the description's additional behavior is what matters: each request returns different random symbols, and the tool supports one or multiple interpretations. This clarifies the non-deterministic nature, which is genuinely useful beyond the structured metadata.

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 description is front-loaded with the core behavior, but it is somewhat repetitive: 'random dream symbols' appears multiple times, and the use-case list is longer than necessary. It is acceptable but not tight enough to be a model of concise documentation.

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

Completeness5/5

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

Given the tool's simplicity, the fully documented parameters, read-only annotations, and existing output schema, the description supplies enough context: what the endpoint returns, how many, and when it is useful. Nothing essential is missing for an agent to call it correctly.

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 count and compact both well documented. The description adds only a general notion of 'one or multiple' but does not improve on the schema's detailed parameter meanings, so the baseline score of 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?

The description clearly states the tool's function: returning random dream symbols with interpretations from a 2,000+ symbol database. The word 'random' plus the discovery framing distinguishes it from the sibling lookup tools such as get_dreams_symbols_id, so an agent can tell what this endpoint is for.

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?

The description offers clear use cases like dream-of-the-day features, journaling prompts, and meditation on subconscious themes. However, it never says when not to use this tool or explicitly points to siblings for specific symbol lookups, leaving the alternative selection implied rather than stated.

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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