web search
get_api_v1_webweb search Billing per call: 1 Credits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| s | No |
get_api_v1_webweb search Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| s | No |
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?
There are no annotations, so the description carries full responsibility for behavioral disclosure. It only mentions billing cost ('Billing per call: 1 Credits') and omits details about result format, response behavior, authentication, or side effects.
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 extremely short and not verbose, but the phrase 'web search' is redundant with the title. The billing note is useful, though the missing punctuation and lack of a complete sentence reduce clarity.
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?
With no annotations, no output schema, and only one minimal line of description, the tool is underspecified. The billing cost is disclosed, but what the search returns and how to use it correctly are not covered, leaving an AI agent without enough context.
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?
Schema description coverage is 0%, and the description does not explain the 's' parameter. While the schema title 'search term' and example 'python learning' help, the description itself adds no parameter-meaning context beyond the schema.
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 is 'web search', which simply restates the title and adds no verb or specific resource context. It does not explain what the tool actually does beyond the title, making it essentially tautological.
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?
No guidance is provided about when to use this tool over the sibling tools get_api_v1_images or get_favicon. The description offers no context, prerequisites, or exclusions.
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 targets a distinct purpose: web search, image search, and favicon retrieval. There is no real overlap or ambiguity between them.
The tool names mostly follow a consistent get_ prefix and snake_case style. However, get_api_v1_images and get_api_v1_web include the API version while get_favicon does not, creating a minor inconsistency.
Three tools is well-scoped for a search-focused server. Each tool covers a distinct and useful search-related capability without unnecessary bloat.
The server covers the core search domain with web search, image search, and favicon lookup. It could arguably include more search verticals like news or video, but the provided surface is functional and not severely incomplete.