kops

by kaka-milan-22

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.2
Disambiguation5/5
Each tool serves a distinct read-only purpose: describe details, list events, get summarized resources, inventory cluster snapshot, fetch logs, and triage diagnostics. No overlap.
Naming Consistency5/5
All tools follow the consistent pattern 'k8s_<verb or noun>' using lowercase and underscores. While some names are nouns (events, inventory, triage), they clearly describe the action and maintain alignment.
Tool Count5/5
With 6 tools, the set is well-scoped for a Kubernetes read-only diagnostic server, covering the essential operations without being over- or under-inclusive.
Completeness5/5
The tool set comprehensively addresses common diagnostic tasks: listing, describing, logs, events, inventory, and triage. No obvious gaps for read-only operations.
Average 4.8/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- Last stable release on June 27, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavior: idempotent, non-mutating, output truncated to ~50 KB, and raises errors on kubectl failures. This is comprehensive.
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 front-loaded with purpose and safety, but the bulleted Args list is somewhat redundant with the schema. It could be trimmed, but it's not excessively long.
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?
Given 7 parameters, no annotations, but an output schema exists, the description covers errors, truncation, idempotency, and usage constraints. It is complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description adds minimal new meaning. The Args section mostly restates schema info. Some nuance like 'hard max 1000' is present but also in schema.
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 'Fetch logs from a pod' and emphasizes it is read-only and idempotent, distinguishing it from sibling tools like k8s_describe or k8s_get. The verb and resource are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates when to use (for pod logs) and provides error conditions (pod NotFound, Forbidden). It lacks explicit when-not or alternatives, but the context is clear given sibling tools have distinct purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: read-only (runs kubectl get -o json only), idempotent, never creates/mutates/deletes, returns summarized output, excludes Secret/ConfigMap values, and raises on failures. This is comprehensive and exceeds the burden.
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 well-structured, starting with purpose then behavioral details, followed by parameter list. It is informative yet concise, though some redundancy exists (e.g., repeating namespace pattern) that could be trimmed.
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?
Given the tool's complexity, 100% schema coverage, and presence of output schema, the description is complete. It covers behavior, permissions, limitations, output format, and cross-references sibling tools, leaving no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds some context (e.g., common kind examples, effect of omitting namespace/name, selector ignored when name given) but does not significantly extend beyond what the schema already provides.
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 the tool lists or fetches K8s resources (specific verb+resource) and summarizes key fields. It differentiates from the sibling k8s_describe by noting that k8s_get provides summarized output while k8s_describe offers deeper detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use (read-only operations), that it is safe to call repeatedly, and provides clear alternative: for deeper detail use k8s_describe. It also notes prerequisites (kubeconfig with read/list access) and error conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states it is read-only, idempotent, and never mutates the cluster. It also notes requires read access and raises on kubectl failure. With no annotations provided, the description fully covers behavioral transparency.
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 concise and well-structured. It starts with the main purpose, then provides key traits, use cases, and a clear argument list. Every sentence adds value; no redundancy.
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?
Given the tool has 5 parameters (all optional), 100% schema coverage, and an output schema, the description provides sufficient guidance to use the tool effectively. It covers purpose, behavior, error conditions, and parameter usage.
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 coverage is 100%, so baseline is 3. The description adds context: namespace ('omit for cluster-wide'), kind ('capitalized as K8s reports it'), name ('use with kind'), since (format and default), context ('omit to use current context'). This enriches understanding beyond the schema.
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 the tool lists recent K8s events, most recent first. It specifies it is read-only and lists events only, effectively distinguishing it from sibling tools like k8s_get or k8s_describe. The purpose is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear use cases (scheduling failures, image pull problems, etc.) and explains that events can be filtered by namespace and involved object. However, it does not explicitly mention when not to use this tool versus alternatives, which would strengthen guidance further.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the burden of behavioral disclosure. It clearly states the tool is read-only, idempotent, runs kubectl describe, never mutates the cluster, requires read access, and raises on kubectl failure (e.g., NotFound, Forbidden). It also notes the output is truncated text (~30 KB).
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 concise and well-structured. The first two lines state purpose and key characteristics, followed by a bullet list of arguments. Every sentence adds value, with no redundancy or unnecessary detail.
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?
Given the tool's complexity (4 parameters, output schema exists, sibling tools present), the description is complete. It covers when to use, behavioral traits, parameter semantics, and output format. No gaps are evident.
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 coverage is 100%, so baseline is 3. The description adds value beyond schema by explaining the kind parameter is the same set as k8s_get, the name is required with no glob/partial matching, and context/namespace can be omitted for current context or cluster-scoped kinds. This provides helpful usage context.
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?
Description begins with a clear statement of purpose: 'Describe a single K8s resource (text output from kubectl describe).' It then notes it is read-only and idempotent, distinguishing it from mutation tools. The sibling tools include k8s_get, and the description explicitly says 'Use when k8s_get isn't enough,' providing clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: 'Use when k8s_get isn't enough — describe shows events, conditions, container details, volume mounts, image pull state, etc.' It also notes it requires read access and raises on failure, guiding the agent on preconditions and errors.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses read-only behavior, idempotency, silent skipping of forbidden/absent resources, exclusion of pods (counts only), and that ConfigMap/Secret values are never returned.
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?
Well-structured with clear sections, front-loaded with purpose and key constraints. Slightly verbose but every sentence contributes; minor redundancy could be trimmed.
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?
For a complex 5-parameter tool with no output schema, the description covers all relevant behavioral details, modes, exclusions, defaults, and edge cases, making it complete for effective agent use.
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?
Schema coverage is 100%, and the description adds significant value: explains mode payload sizes, reasons for default exclusion of config resources, and behavior of Istio auto-detection, all beyond basic schema 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 it is a 'One-shot comprehensive cluster snapshot' for documentation/audits, and explicitly differentiates from sibling tools like k8s_triage (pod health) and k8s_get (specifics).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (broad visibility, audits) and when-not (pod specifics), includes mode guidance ('full' vs 'overview'), and references specific alternatives (k8s_triage, k8s_get).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only nature ('fans out several kubectl get calls only — never mutates the cluster, idempotent'), permission requirements, and error behavior ('Forbidden/absent are skipped rather than aborting'). No annotations provided, but description carries full burden effectively.
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?
Concise and well-structured: star emoji + bold header, bullet list of returns, behavioral paragraph, usage guidance, and parameter details. Every sentence adds value; no fluff.
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?
Given 3 optional parameters and no output schema, description adequately explains what the tool returns (four categories) and how to use it. All necessary context (permissions, idempotency, error handling) is included.
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?
Schema covers all 3 parameters with descriptions (100% coverage). Description's Args section adds default values, format constraints (e.g., '1h', '30m'), and clarifies namespace scoping. Adds value beyond schema.
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?
Description starts with 'Start here for cluster diagnostics' and lists specific outputs (problem pods, warning events, unhealthy nodes, stale deployments). It distinguishes itself from siblings by stating it's the first tool for broad questions, then deeper with k8s_describe/k8s_logs/k8s_events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance: 'Use this as the FIRST tool for broad questions... then dig deeper with k8s_describe / k8s_logs / k8s_events.' Also states read-only and cluster-wide read access needed, with graceful handling of forbidden sub-queries.
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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