Spotinst MCP Server

by arnstarn

Overview Schema Source Related Servers Discussions Admin

Python

Remote

get_cluster_log

Retrieves scaling and activity log events for an Ocean cluster (AWS or Azure) with date range and severity filters.

Instructions

Get scaling and activity log events for an Ocean cluster (AWS or Azure).

Args: cluster_id: The Ocean cluster ID (e.g. o-abc12345) from_date: Start date in YYYY-MM-DD format (e.g. 2026-03-19) to_date: End date in YYYY-MM-DD format (e.g. 2026-03-20) severity: Filter by severity: ALL, INFO, WARN, ERROR (default: ALL) limit: Max number of log entries (default: 500) account_id: Optional account ID to query. Defaults to SPOTINST_ACCOUNT_ID env var. cloud: Cloud provider: aws or azure (default: aws)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "cluster_id": "<cluster_id>",
      "from_date": "<from_date>",
      "to_date": "<to_date>"
    },
    "name": "get_cluster_log"
  }
}

Input Schema

Name	Required	Default
`cluster_id`	Yes
`from_date`	Yes
`to_date`	Yes
`severity`	No	ALL
`limit`	No
`account_id`	No
`cloud`	No	aws

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 21, 2026

TDQS

B3.4/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It fails to mention side effects (none expected), authentication requirements, rate limits, or potential empty results. The description only lists parameters and defaults, omitting critical behavioral traits for a read-only log tool.

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

Conciseness4/5

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

The description is structured as a clear docstring with a one-line summary followed by an enumerated Args list. It is concise, uses consistent formatting, and includes examples inline. No redundant sentences, though the Args block could be slightly more streamlined (e.g., merging defaults into one line).

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 the output schema exists, return values need not be explained. However, the description lacks context about log severity meanings, date range boundaries, or pagination behavior. For a tool with 7 parameters and no output schema details, completeness is adequate but not thorough.

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?

Schema description coverage is 0%, so the description's parameter explanations add significant value. It provides format examples for dates (YYYY-MM-DD), a cluster ID example (o-abc12345), severity options (ALL, INFO, WARN, ERROR), default values, and the account_id fallback to environment variable. This compensates well for the schema's lack of descriptions.

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 'Get scaling and activity log events for an Ocean cluster', specifying both AWS and Azure. It identifies the resource (cluster logs) and action (get), distinguishing it from siblings like get_cluster (cluster details) or get_cluster_health (health status).

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 explicit guidance on when to use this tool versus other log or monitoring tools. The description does not mention when it's appropriate to query logs, nor does it exclude alternatives like get_cluster_costs or get_cluster_scheduling. The agent must infer usage from context.

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