get_database_cluster_components
Retrieve components of a database cluster by providing its namespace and name.
Instructions
Get components of a specific database cluster.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| namespace | Yes |
Retrieve components of a database cluster by providing its namespace and name.
Get components of a specific database cluster.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| namespace | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It does not mention whether the operation is read-only, what happens if the cluster does not exist, or any side effects. The description lacks essential behavioral context for an AI agent.
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 extremely brief (one sentence), which is concise but borderline under-specified. It front-loads the core action and resource, but the brevity leaves out critical details, making it mediocre rather than optimal.
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 no output schema, no annotations, and 0% parameter coverage, the description is severely incomplete. It does not explain what the components are, how they are structured, or any constraints like required permissions, making it inadequate for correct tool invocation.
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 0%, and the description does not explain the purpose or expected values of the 'name' and 'namespace' parameters. It adds no meaning beyond the schema, failing to help the agent understand what values to provide.
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 action 'Get components' and the resource 'database cluster'. However, it does not explicitly distinguish from sibling tool 'get_database_cluster', which likely retrieves the cluster itself. The specificity is good but could be enhanced by contrasting with similar tools.
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?
No guidance on when to use this tool versus alternatives like 'get_database_cluster' or 'list_database_clusters'. The description provides no context for appropriate usage scenarios or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/spron-in/mcp-everest'
If you have feedback or need assistance with the MCP directory API, please join our Discord server