Dataverse MCP Server

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

No annotations are provided, so the description carries full burden. It mentions 'filtering options' and 'publisher information,' which adds some behavioral context, but fails to disclose critical traits: whether this is a read-only operation, potential rate limits, pagination behavior (implied by 'top' parameter but not explained), or error conditions. For a list tool with no annotations, this leaves significant gaps in understanding how it behaves.

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 appropriately sized (three sentences) and front-loaded with the core purpose. Each sentence adds value: the first states the action, the second gives usage scenarios, and the third notes included data. There's minimal waste, though it could be slightly more structured (e.g., bullet points for usage cases).

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 moderate complexity (list operation with 2 parameters), no annotations, and no output schema, the description is adequate but incomplete. It covers the 'what' and 'why' but misses behavioral details (e.g., safety, performance) and output format. For a tool in a Dataverse context with many siblings, more guidance on typical use cases or limitations would enhance completeness.

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 both parameters ('includeManaged' and 'top') fully. The description adds marginal value by implying filtering (via 'filtering options') and mentioning 'unmanaged solutions' (related to 'includeManaged'), but doesn't provide additional syntax, format, or examples beyond what the schema states. Baseline 3 is appropriate when 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 clearly states the tool's purpose: 'Retrieves a list of solutions in the Dataverse environment with filtering options.' It specifies the verb ('retrieves'), resource ('solutions'), and scope ('Dataverse environment'), and distinguishes from siblings like 'get_dataverse_solution' (singular) by emphasizing listing. However, it doesn't explicitly contrast with other list_* tools (e.g., list_dataverse_tables), so it's not a perfect 5.

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 implied usage scenarios: 'Use this to discover available solutions, find unmanaged solutions for customization, or get an overview of solution packages.' This gives context but lacks explicit when-not-to-use guidance or named alternatives. For example, it doesn't clarify if 'get_dataverse_solution' should be used for detailed info on a specific solution, leaving some ambiguity.

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