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Crowdin MCP by usefulapi

List source strings

crowdin_list_strings
Read-only

List source strings in a project (id, text, identifier, context). Crowdin API: GET /projects/{projectId}/strings.

Input Schema

NameRequiredDescriptionDefault
croqlNoCrowdin Query Language filter, e.g. count of words <= 5.
limitNoMax rows (max 500, default 25).
fileIdNoFilter by source file id.
filterNoFilter strings by text or identifier substring.
offsetNoRows to skip (default 0).
branchIdNoFilter by branch id.
projectIdYesNumeric project id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds the underlying API endpoint (GET /projects/{projectId}/strings) and the shape of returned fields, which is modest extra context, but says nothing about pagination semantics, ordering, or how croql/filter narrowing affects results.

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?

Two short clauses, front-loaded with the purpose and followed by the returned fields and endpoint. No filler, though the parenthetical field list is of limited value given the absence of an output schema for those fields.

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 read-only listing tool with full schema coverage and annotations covering safety, the description supplies enough to call it correctly. Minor gaps remain: no output schema, so return shape relies on the parenthetical list, and pagination behavior is left implicit.

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%, so all seven parameters are already documented in the schema, including filter, croql, limit, and offset. The description adds no parameter-level meaning beyond the returned field list, so the baseline of 3 applies.

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?

States a specific verb and resource ('List source strings in a project') and even enumerates the returned fields (id, text, identifier, context). It is distinguishable from siblings like crowdin_list_files or crowdin_list_branches by resource, though it never names an alternative explicitly.

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 implied rather than stated: an agent can infer this is the read path for enumerating strings in a project. There is no when-to-use/when-not guidance, no mention of the filtering parameters as selection criteria, and no routing to siblings such as crowdin_add_string or crowdin_get_language_progress.

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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