Get available modules for translation in a project.
Args: project_key: Project key (tenant ID). Uses global tenant_id if not provided
Returns: JSON string with available modules including module names and IDs
| Name | Required | Description | Default |
|---|---|---|---|
| project_key | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the parameter fallback behavior and the return format (JSON string with module names and IDs), but does not mention potential errors, authentication needs, or other behavioral nuances. This is adequate for a read-only tool but not deeply transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise: a single-sentence summary followed by brief Args and Returns sections. Every sentence adds value with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one optional parameter and an output schema, the description covers purpose, parameter semantics, and return value. It could mention error conditions or alternative uses, but for a simple getter it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It adds meaning to 'project_key' by explaining it is a 'Project key (tenant ID)' and describes the fallback behavior when not provided. This goes beyond the schema's bare property definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get available modules for translation in a project.' It uses a specific verb ('Get') and resource ('available modules'), distinguishing it from sibling tools like 'get_translation_languages' (which gets languages) and 'get_module_keys' (which gets module keys).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context (for translation in a project) and notes the default behavior for project_key ('Uses global tenant_id if not provided'). It doesn't explicitly exclude alternatives, but for a simple getter this level of context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are organized into clear domains (auth, roles, schemas, translations, projects), and within each domain, tools have distinct purposes (e.g., get_schema vs list_schemas, save_captcha_config vs update_captcha_status). A few pairs like get_auth_status and get_authentication_config could cause minor confusion, but their descriptions clarify the difference.
All tool names follow a consistent verb_noun pattern in snake_case, using predictable verbs like get, list, create, update, set, enable, and configure. Even longer names like save_module_keys_with_translations adhere to the same convention, with no mixed casing or arbitrary styles.
With 36 tools, the server exceeds the typical well-scoped range for MCP servers. While the broad platform domain justifies some breadth, the sheer volume can overwhelm agents and suggests the toolset could be consolidated or split into smaller, focused servers.
The toolset provides decent coverage for creation, listing, and some updates across entities like permissions, roles, schemas, and translations. However, there are notable gaps: no delete operations for most resources, no role update, and no project update/delete, which leaves lifecycle management incomplete.
