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OpenShift 4 MCP Server

get_pod_logs

Fetch logs from a specific pod's container to diagnose issues or monitor output. Supports namespace, previous instances, tail lines, and time-based filters.

Instructions

Fetch logs from a pod container.

Args: name: Pod name. namespace: Namespace (default: "default"). container: Container name (empty = first/only container). previous: Return logs from the previous container instance. tail_lines: Number of lines from the end (default 100, 0 = unlimited). since_seconds: Only return logs newer than this many seconds. cluster: Named cluster to target (empty = default).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
clusterNo
previousNo
containerNo
namespaceNodefault
tail_linesNo
since_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It provides concrete semantics for parameters – container empty resolves to first/only container, previous reads the prior instance, tail_lines 0 means unlimited, and since_seconds filters by age. It does not explicitly state safety or side-effect profile, but 'Fetch' clearly indicates a read operation.

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 compact purpose sentence followed by a focused Args list. Each parameter line adds unique information not present in the schema titles, and there is no filler or repetition.

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

Completeness5/5

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

The tool has a moderate parameter count, an output schema exists, and the description covers parameter semantics and defaults. An agent has all necessary parameter context to invoke the tool correctly; the only missing element is sibling comparison, which belongs under usage guidelines rather than this dimension.

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

Parameters5/5

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

The input schema has 0% description coverage, so the description must define each parameter. It does so comprehensively: every one of the 7 parameters has an inline explanation covering defaults and edge cases (e.g., '0 = unlimited', 'empty = first/only container'), making the schema's opaque defaults meaningful.

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 opens with 'Fetch logs from a pod container' – a specific verb and resource. This clearly distinguishes it from siblings like get_build_logs, describe_pod, and exec_in_pod, and the parameter list confirms it targets pod logs with filtering options.

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

Usage Guidelines3/5

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

No explicit when-to-use or alternative guidance appears in the description. The intended use is implied by the purpose and parameter names, but there are no exclusions or comparisons with close siblings such as get_build_logs or list_events, leaving the agent to infer when this tool should be preferred.

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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