Finds and describes real-world use cases or customer stories for a specific Vonage product. Use this when the user asks for examples of how a product is used in a specific industry or for a particular purpose.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The Vonage product (e.g., 'Video API', 'Voice API', 'Messages API'). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses that the tool 'finds and describes' content, implying a read-only operation, but it does not mention limitations, output format, or edge cases. The description is adequate 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 consists of two sentences with no filler: the first states the function, the second gives usage context. Every word earns its place, making it concise and well-structured.
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 one-parameter tool with no output schema, the description covers purpose, usage context, and parameter semantics. It does not explicitly describe return format or failure behavior, but the phrase 'finds and describes' implies the output. Overall, it is adequately complete for a tool of this complexity.
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 describes the single parameter 'query' as 'The Vonage product (e.g., 'Video API', 'Voice API', 'Messages API')' with 100% coverage. The description adds no extra semantic meaning beyond the schema, so the baseline score of 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 tool's function: finding and describing real-world use cases or customer stories for a specific Vonage product. Uses a specific verb ('finds and describes') and resource ('use cases or customer stories'), distinguishing it from siblings like vonage_api_reference or vonage_tutorial_finder.
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 explicitly says 'Use this when the user asks for examples of how a product is used in a specific industry or for a particular purpose,' providing clear usage context. However, it does not explicitly mention alternative tools or when not to use it.
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.
Each tool has a well-defined, distinct purpose: API reference for endpoint details, code generator for snippets, docs search for general queries, SDK info for SDK specifics, troubleshooter for errors, tutorial finder for tutorials, and use case examples for real-world applications. Despite some potential overlap between search, tutorials, and use cases, the descriptions clearly delineate when to use each.
All tool names follow the consistent pattern 'vonage_' followed by a descriptive noun or noun phrase (e.g., api_reference, code_generator, docs_search). This makes the tool set predictable and easy to understand.
With 7 tools, the server is well-scoped. Each tool covers a distinct aspect of Vonage documentation (search, reference, code, SDK, troubleshooting, tutorials, use cases), and there are no redundant or unnecessary additions.
The tool set provides broad coverage of the documentation domain: finding docs, looking up API references, generating code, getting SDK info, troubleshooting, locating tutorials, and exploring use cases. There are no obvious gaps that would hamper common documentation tasks.
