IGN API Carto MCP Server

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

Annotations already indicate read-only, open-world, idempotent, and non-destructive behavior. The description adds valuable context beyond this: it discloses the data source (FranceAgriMer based on INAO data), notes that an IGN API key is required (with a link to obtain one), and specifies the return format (GeoJSON FeatureCollection with specific attributes). This enriches the agent's understanding of authentication needs and output structure.

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 well-structured and appropriately sized. It starts with a clear purpose statement, followed by data source info, a concise Args section, Returns details, practical examples, and a necessary note about API key requirements. Each sentence adds value without redundancy, making it efficient and easy to parse.

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 (spatial query with authentication), the description is complete. It covers purpose, data source, parameters (with schema doing heavy lifting), return format, examples, and authentication requirements. Although there is no output schema, the description adequately explains the GeoJSON FeatureCollection structure, making it sufficient for agent use.

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 parameters thoroughly. The description adds minimal value beyond the schema: it briefly mentions the 'geom' parameter as 'GeoJSON geometry to intersect' and notes the API key requirement, but does not provide additional syntax or format details. This meets the baseline for high schema coverage.

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: 'Query wine appellation zones (AOC, IGP, VSIG) in France.' It specifies the exact resource (wine appellations), geographic scope (France), and types (AOC/IGP/VSIG). This distinguishes it from sibling tools that handle administrative limits, cadastre, communes, etc., making the purpose specific and well-differentiated.

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 for when to use this tool through examples ('What wine appellations cover this vineyard?' and 'Find AOC zones in Bordeaux region'), which implicitly guides usage for spatial queries about wine appellations. However, it does not explicitly state when NOT to use it or name alternatives among sibling tools, though the examples help infer appropriate scenarios.

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