Give your AI agent access to 150+ translators covering fictional languages, pop culture dialects, historical languages, technical encodings, and internet slang.
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Tool access control
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 3.6/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one lists available translators, the other performs a translation. There is no overlap or ambiguity between them.
Both tool names follow a hyphenated verb-object pattern with a '-tool' suffix, which is consistent. However, 'list-all-translations-tool' actually lists translators, not translations, creating a slight terminology inconsistency.
With only two tools, the server feels minimal and borderline. While these two tools are essential for the translation domain, the count is on the low end and may feel thin for a broader utility.
The core workflow of listing translators and performing translations is fully covered. Minor gaps include no direct way to fetch translator details, but the list function likely provides sufficient context.
list-all-translations-toolList All Translations ToolAList all the translators available in the system. Result is a paged structured response.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| perPage | Yes | Number of translators returned in this paged response |
| totalCount | Yes | Total Translators available |
| currentPage | Yes | Current page number of this paged response |
| translators | Yes | Translators List |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the safety profile is established. The description adds behavioral context by stating the result is 'a paged structured response,' which is useful beyond the annotations. No contradictions, but it does not explain pagination mechanics like page size or cursor handling.
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 a single concise sentence that immediately states the action and result format, with no filler or redundancy. It front-loads the purpose and efficiently conveys the key information.
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 simple list tool with no parameters and an existing output schema, the description covers the core purpose and mentions paging. It does not specify ordering or filtering, but these are likely handled by the output schema. The only notable gap is the title/description mismatch, but the tool is otherwise adequately described.
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?
There are no parameters in the input schema, so schema coverage is 100%. Per the rubric, 0 parameters yields a baseline of 4. The description appropriately does not add parameter-specific details because none exist.
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 uses the specific verb 'List' and clearly identifies the resource ('translators available in the system'). It distinguishes from the sibling 'translate-tool' by focusing on enumeration rather than translation. The title says 'translations' but the description says 'translators', which is a minor inconsistency, but the intended purpose is unambiguous.
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 no guidance on when to use this tool over alternatives. There is no mention of the sibling 'translate-tool' or any conditions or exclusions for use. The usage is implied at best, but no explicit context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
translate-toolTranslate ToolBTranslate the given text using the translator specified and return the result.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The translator to use. Supply the translator slug. | |
| text | No | The text to translate. |
| Name | Required | Description |
|---|---|---|
| text | Yes | Input Text |
| translated | Yes | Translated Text |
| translator | Yes | Translator used |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety and repeatability profile. The description adds no additional behavioral context beyond the trivial 'return the result'—no error handling, slug validation, or side-effect details. Since no extra transparency is provided beyond the annotations, a low score is warranted.
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 a single concise sentence that front-loads the action and result. No filler or redundant information. It earns its place efficiently.
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 only two parameters, a provided output schema, and clear annotations, the description covers the basic contract. However, it omits a hint that valid translator slugs might need to be discovered (e.g., via list-all-translations-tool) and does not specify behavior for missing text or invalid slug. Given the low complexity, the description is mostly complete but could be slightly stronger.
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 input schema has 100% description coverage: slug is described as 'The translator to use. Supply the translator slug.' and text as 'The text to translate.' The description merely restates these concepts ('translator specified', 'given text') without adding meaning beyond the schema. Baseline 3 is appropriate.
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 action ('Translate'), the object ('given text'), and the mechanism ('using the translator specified'), and implies a result is returned. It is distinguishable from the sibling list-all-translations-tool, which lists translations rather than performing them, though it does not explicitly reference the sibling.
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 no guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. The existence of sibling list-all-translations-tool is not leveraged to direct the agent when to translate versus list. Usage is only implied by the tool's name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
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If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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