Enable or disable a CAPTCHA configuration.
Args: item_id: The ID of the CAPTCHA configuration to update is_enable: True to enable, False to disable the configuration project_key: Project key (tenant ID). Uses global tenant_id if not provided
Returns: JSON string with status update result
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | ||
| is_enable | Yes | ||
| 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 must disclose behavioral traits on its own. It explains the project_key fallback and indicates the return type ('JSON string with status update result'), which adds useful context. However, it does not mention side effects, idempotency, permissions, or error behavior—common expectations for a mutation tool.
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 tightly structured: a one-line action summary, followed by a compact Args list and a Returns statement. Every sentence earns its place—no redundancy, no filler, and the most important information is front-loaded.
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?
Given the tool's simplicity (a status toggle with three parameters), the description covers the essential aspects: what it does, the parameter meanings, and the return type. It lacks explicit error scenarios or preconditions, but the output schema exists and the operation is straightforward, so the gap is acceptable. A 5 would require more detail on edge cases or side effects.
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 zero property descriptions, so the Args section shoulders the entire explanatory burden. It does excellent work: item_id is identified as the config ID, is_enable is clearly mapped to True/False, and project_key is explained as a tenant ID with a global fallback. This far exceeds what the schema alone communicates.
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 opens with a specific verb-resource pair: 'Enable or disable a CAPTCHA configuration.' This clearly distinguishes the tool from siblings like save_captcha_config and list_captcha_configs by focusing solely on status toggling.
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 one-line summary makes the intended use obvious: to turn a CAPTCHA config on or off. It does not explicitly mention alternatives or exclusions, but the contrast with sibling tool names (e.g., save_captcha_config) implies that this tool is specifically for status changes, not full config editing.
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.
