Google Images Remote MCP Server

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

No annotations are provided, so the description carries the behavioral burden. It clearly discloses that this is a scraping operation, lists the advanced filters, mentions page-based pagination via 'ijn', and enumerates the returned fields. It does not cover rate limits, authentication, or failure behavior, but it gives a solid behavioral picture.

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 front-loaded with the core action, then the output shape, then use cases. It is slightly longer than strictly necessary because of the use-case list, but each sentence contributes either behavioral clarity or usage guidance. It is well-structured and avoids redundancy with the schema.

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?

Given the tool has 11 parameters, no output schema, and no annotations, the description does a good job of summarizing what the tool returns and what filters are available. It does not mention error behavior, result count, or rate limits, but it covers the essential information an agent needs to select and invoke the tool.

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 baseline is 3. The description adds value beyond the schema by grouping the filters into categories (size, color, image type, safesearch, domain/country/language, device type) and explicitly naming the pagination parameter 'ijn'. This helps an agent understand how the many parameters relate to each other.

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 opens with a specific verb and resource: 'Scrapes Google Images for a query.' It clearly distinguishes this from the many sibling search tools by focusing on image-specific results and explicitly listing image return fields like thumbnail, dimensions, and source domain. The name is also self-descriptive, but the description goes beyond it.

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 a clear context of when to use the tool by enumerating use cases such as visual-asset discovery, reverse-image workflows, dataset collection, and brand monitoring. It does not explicitly state when not to use it or name alternative sibling tools, so it misses the full 'when-not/alternatives' bar.

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