Dream Interpretation MCP Server by RoxyAPI

Symbol counts by letter - Dream dictionary index API

get_dreams_symbols_letters

Read-only

Get the count of dream symbols available for each letter A-Z. Build alphabetical dream dictionary navigation to help users browse dream interpretations by letter, from abandonment dreams to zodiac dreams. See how many dream meanings exist for each starting letter.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`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
`total`	Yes
`letters`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "letters": {
+      "additionalProperties": {
+        "type": "number"
+      },
+      "type": "object"
+    },
+    "total": {
+      "type": "number"
+    }
+  },
+  "required": [
+    "letters",
+    "total"
+  ],
+  "type": "object"
+}

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

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the behavioral detail that it returns counts grouped by starting letter, but does not disclose things like whether zero-count letters are included or how the response is ordered. Given an output schema exists, this is acceptable but not rich.

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

Conciseness4/5

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

The description is three sentences and front-loads the core purpose in the first sentence. The illustrative phrase 'from abandonment dreams to zodiac dreams' is mildly colorful but not excessive, and the rest is informative without redundancy.

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 simple, zero-required-parameter read-only tool with an output schema, the description provides enough context to understand the purpose and use case. It does not need to explain return values because an output schema is present, and annotations cover safety.

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?

The only parameter, compact, is fully documented in the input schema with a clear description of its shape and token savings. Schema description coverage is 100%, so the description does not need to repeat parameter details. It adds no additional parameter semantics, matching the baseline.

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 states a specific verb and resource: 'Get the count of dream symbols available for each letter A-Z.' It also clarifies the intended structure (alphabetical letters) and distinguishes it from siblings like get_dreams_symbols by focusing on per-letter counts for dictionary navigation.

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 a concrete use case: 'Build alphabetical dream dictionary navigation to help users browse dream interpretations by letter.' It implies when to use this tool versus the general symbol endpoints, though it does not explicitly name alternatives or say when not to use it.

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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