Skip to main content
Glama
zhouweico

mcp-kubevela

by zhouweico

vela_list_targets

Read-onlyIdempotent

List KubeVela delivery targets (cluster and namespace pairs) to identify available deployment destinations. Supports pagination and filtering by project for easy navigation.

Instructions

列出交付目标(target,即集群+命名空间组合)。

对应 API:GET /api/v1/targets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
page_sizeNo
project_nameNo按项目过滤
response_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the API method (GET) and clarifies the target definition, but it does not disclose pagination behavior, response format nuances, or any other operational details. Since annotations cover the key behavioral traits, a score of 3 is appropriate.

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 extremely concise—two sentences that state exactly what the tool does and the corresponding API. No redundant words, no filler. It earns a top score for efficiency and front-loading.

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?

Given that this is a straightforward listing tool with an output schema and strong annotations, the description is minimally adequate. It defines the resource and API, and the output schema covers return structure. However, it lacks usage guidance and parameter explanation, and does not differentiate from sibling tools, leaving some gaps for a fully contextual understanding.

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

Parameters2/5

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

The description does not mention parameters at all. Schema coverage is only 25% (only project_name has a description), so the description should compensate by explaining parameter meanings, but it does not. The agent must rely solely on the schema's sparse descriptions and defaults, leaving page, page_size, and response_format ambiguous.

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: listing delivery targets, and defines 'target' as a cluster+namespace combination. It also gives the corresponding API endpoint, adding specificity. However, it does not distinguish itself from the sibling tool 'vela_list_project_targets', so it falls short of a 5.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention any prerequisites, exclusions, or why one would prefer this over 'vela_list_project_targets' or other list tools. This leaves the agent without decision support.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/zhouweico/mcp-kubevela'

If you have feedback or need assistance with the MCP directory API, please join our Discord server