Lara Translate MCP Server

get_glossary_counts

Read-onlyIdempotent

Retrieve term and language counts for a glossary in your Lara Translate account to monitor glossary size and language coverage.

Instructions

Retrieves the term and language counts for a glossary in your Lara Translate account.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_glossary_counts"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	The glossary ID (format: gls_*, e.g., 'gls_xyz123')

Output Schema

Name	Required	Description	Default
`unidirectional`	No	Entry counts keyed by language code for unidirectional glossaries
`multidirectional`	No	Total entry count for multidirectional glossaries

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv2.0.0Sep 29, 2026
- removedOutput schema / additionalProperties
```
Removed value: -{}
```

Changed1 schema field changedv1.0.4May 29, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "multidirectional": {
+      "description": "Total entry count for multidirectional glossaries",
+      "type": "number"
+    },
+    "unidirectional": {
+      "additionalProperties": {
+        "type": "number"
+      },
+      "description": "Entry counts keyed by language code for unidirectional glossaries",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    }
+  },
+  "type": "object"
+}

Addedv1.0.2May 4, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered by structured data. The description adds no behavioral context beyond the annotations — no error handling for an unknown/invalid glossary ID, no note on auth requirements, and no indication of what units the counts use.

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?

One sentence, no filler, and the resource scope is front-loaded. It is appropriately sized for a simple single-parameter read tool, though it is too terse to convey any usage or behavioral nuance.

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?

An output schema exists, so return values need no explanation, and the annotations plus the fully documented single parameter cover the rest. For a one-parameter read-only tool this is nearly complete; only error behavior for an invalid ID is left unspecified.

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%: the single id parameter is documented with its gls_* pattern and example, and the description adds no format, constraint, or semantics beyond that. Baseline 3 applies when the schema already does the heavy lifting.

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 gives a specific verb ("Retrieves") and a precise resource ("term and language counts for a glossary"), which clearly separates it from the broader get_glossary sibling that returns glossary details. It does not name a sibling explicitly, so it stops short of a 5.

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?

Usage is only implied: an agent can infer you call this when you need counts rather than full glossary data, but the description never states when to prefer it over get_glossary (which may already surface counts) or after operations like add_glossary_entry. No prerequisites or exclusions are given.

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