search_webSearch the web via SerpAPI (Google search). Returns organic results with rankings. Costs $0.01 USDC per call. Requires SERPAPI_KEY env var configured on backend.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search query | |
| limit | No | Max results (default 10, max 20) |
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?
Annotations already declare readOnlyHint, openWorldHint, and destructiveHint false. The description adds value by disclosing the cost per call ($0.01 USDC) and the dependency on SERPAPI_KEY env var, which are important operational details not covered by annotations.
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 three sentences with no filler. It front-loads the purpose and includes only essential details (cost, auth requirement, return type). Every sentence earns its place.
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 tool with two parameters and no output schema, the description adequately conveys return type (organic results with rankings) and operational prerequisites. It doesn't detail error handling or pagination, but that's not critical for this simplicity.
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 coverage is 100% (both q and limit are described in the schema). The description does not add extra meaning beyond what the schema provides, so 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 states a specific verb ('Search the web') and resource ('via SerpAPI (Google search)'), and specifies it returns organic results with rankings. This clearly differentiates it from sibling tools that are racing-specific lookups.
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 context is clear: this is a general web search tool, contrasted with the racing-specific siblings. It doesn't explicitly state when not to use it, but the description and sibling names imply it's for generic queries. No exclusions are needed.
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 clearly distinct purpose: status checks, race search, race results, driver lookup, and web search. The two race-related tools are complementary (search returns subsession IDs used by get_race_results), not overlapping.
All tool names follow the verb_noun snake_case pattern (get_, search_, lookup_). The verbs are appropriate and consistent, with no mixing of conventions or camelCase.
With only 5 tools, the server is well-scoped for its stated purpose as an x402 facilitator offering iRacing data and web search. Each tool earns its place and there is no bloat.
The race search-to-results flow is complete, and driver lookup and web search work standalone. However, lookup_driver requires a customer ID with no way to discover IDs from within the tool set (no driver search by name), leaving a minor gap.