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Qvakk

Terraform Registry MCP Server

by Qvakk

get_latest_provider_version

Retrieve the current version number and metadata for a Terraform provider by specifying its namespace and name, ensuring you use up-to-date provider versions in infrastructure code.

Instructions

Get the latest version of a Terraform provider.

Args:
    namespace: Provider namespace (e.g., 'hashicorp')
    name: Provider name (e.g., 'aws')

Returns:
    Dictionary containing the latest version number and metadata

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceYes
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns a dictionary with version number and metadata, which is helpful, but lacks details on error handling, rate limits, authentication requirements, or whether it's a read-only operation. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 efficiently structured with a clear purpose statement followed by bullet points for arguments and returns. Every sentence adds value without redundancy, making it easy to scan and understand quickly. It's appropriately sized for a simple tool with two parameters.

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

Completeness4/5

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

Given the tool's low complexity (2 simple parameters), no annotations, and the presence of an output schema (which handles return values), the description is mostly complete. It covers the purpose and parameters well, but could improve by adding usage guidelines or behavioral details like error cases. The output schema reduces the need to explain returns in the description.

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?

The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'namespace' is the provider namespace with an example ('hashicorp') and 'name' is the provider name with an example ('aws'), clarifying the purpose and format of each parameter. This compensates well for the schema's lack of descriptions, though it could include more details like constraints or valid values.

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

Purpose4/5

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('latest version of a Terraform provider'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'list_provider_versions' or 'get_provider_details', which might offer similar functionality, preventing a perfect score.

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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'list_provider_versions' and 'get_provider_details' available, there's no indication of when this specific tool is preferred, leaving the agent to guess based on tool names alone.

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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