Google Search MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions the tool fetches full article content and returns consolidated results, it doesn't disclose important behavioral traits like rate limits, authentication requirements, error handling, or what 'consolidated results' actually means in terms of output format. For a tool that performs external API calls and content fetching, this is a significant gap.

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 perfectly concise and well-structured in just two sentences. The first sentence explains the complete workflow, and the second sentence provides the optimization context. Every word earns its place with no redundancy or unnecessary elaboration.

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 no annotations and no output schema that performs external API calls and content fetching, the description is incomplete. It doesn't explain what the output looks like (what 'consolidated results' means), doesn't mention authentication requirements, rate limits, or error conditions. The description should provide more context about the tool's behavior and limitations given the complexity of the operation.

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 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it mentions the general purpose but doesn't provide additional context about parameter usage, interactions, or best practices. The baseline of 3 is appropriate when the schema does all the heavy lifting.

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 purpose with specific verbs ('searches for', 'fetches full article content', 'returns consolidated results') and distinguishes it from siblings by specifying 'optimized for news and current events' and mentioning the Google Custom Search API. It goes beyond just restating the name to explain the full workflow.

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 clear context about when to use this tool ('optimized for news and current events'), which helps differentiate it from the generic 'deep_search' and 'google_search' siblings. However, it doesn't explicitly state when NOT to use it or provide specific alternatives for non-news searches.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.