DataForSEO 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. It states the tool 'gets list of availible locations,' which suggests a read-only operation, but doesn't clarify aspects like authentication needs, rate limits, error handling, or what 'availible' entails (e.g., cached vs. live data). This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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 a single, straightforward sentence that efficiently states the tool's purpose and its relationship to a sibling tool. It avoids unnecessary details or repetition, making it front-loaded and easy to parse. However, minor spelling errors ('availible') slightly detract from polish, but overall, it's appropriately sized with zero waste.

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's complexity (4 parameters, no output schema, and no annotations), the description is insufficiently complete. It lacks details on return values (e.g., format of the location list), behavioral traits like performance or constraints, and differentiation from siblings. While the schema covers parameters well, the overall context for an AI agent to effectively use this tool is incomplete, especially without annotations to fill gaps.

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 has 100% description coverage, with detailed parameter documentation including defaults and enums (e.g., 'search_engine' options, 'location_type' variants). The description adds no additional parameter semantics beyond what the schema provides, such as explaining interactions between parameters or usage examples. Given the high schema coverage, a baseline score of 3 is appropriate as the schema does 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 states the tool is a 'utility tool for serp_organic_live_advanced to get list of availible locations,' which clarifies it fetches location data for a specific sibling tool. However, it's somewhat vague about what 'availible locations' means (e.g., search engine locations, geographic areas) and doesn't explicitly distinguish it from other location-related siblings like 'serp_youtube_locations' or 'kw_data_google_ads_locations,' leaving room for ambiguity in its exact scope.

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 mentions it's a utility for 'serp_organic_live_advanced,' implying usage in that context, but provides no explicit guidance on when to use this tool versus alternatives like 'serp_youtube_locations' or 'kw_data_google_ads_locations.' There are no exclusions, prerequisites, or clear scenarios outlined, making it rely on implied context without actionable advice for an AI agent.

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