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jjohnsen

jaj-dataverse-dev-mcp

by jjohnsen

list_environments

Lists the Dataverse environments configured for access, enabling agents to identify available targets for data operations and development tasks.

Instructions

List the configured Dataverse environments that can be accessed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It implies a read-only listing operation ('configured' and 'can be accessed') but does not disclose potential errors, authentication requirements, or any side effects. For a simple list tool this is acceptable, but it adds no insight beyond the obvious read-only nature.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with zero wasted words. It states exactly what the tool does without any fluff. Perfect conciseness for a tool with no parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters and no output schema, the description is minimal. It does not explain what the returned list contains (e.g., names, IDs, details), nor any pagination or ordering. Since an agent may need to know the format of the result to use it correctly, this is a minor gap. However, given the simplicity, it is marginally adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the schema trivially covers everything. Per the baseline rule, this scores a 4. There is nothing to add in the description since no inputs exist to explain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (List) and the resource (configured Dataverse environments that can be accessed). This distinguishes it from siblings like ping (connectivity), whoami (user identity), and dataverse_request (general request). The specificity of 'configured' and 'can be accessed' adds useful context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. While the purpose is clear, the agent must infer that this is the tool for enumerating environments. There is no mention of when not to use it or any conditions that would route to a sibling.

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

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