@crontinel/mcp-server

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by crontinel

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Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool targets a distinct resource and action: listing vs. getting cron status, queue vs. Horizon status, and alert listing/acknowledgment/creation. Descriptions clearly differentiate overlapping monitoring concepts.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern: list_, get_, acknowledge_, create_. No mixed conventions, making the set predictable and easy to navigate.
Tool Count5/5
Seven tools is well-scoped for a monitoring server, covering the core areas (cron, queues, Horizon, alerts) without unnecessary redundancy.
Completeness4/5
The set covers monitoring and alert management comprehensively, but lacks an update/delete for alert channels and a detail view for individual alerts. Minor gaps that agents can work around.
Average 3.7/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 16 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
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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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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It only states 'create' without mentioning side effects, required permissions, behavior on duplicate channels, or what happens on success/failure.
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 single concise sentence that front-loads the action and resource, with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite comprehensive parameter schema, the tool has no annotations or output schema, and the description omits return values, permissions, and edge-case behaviors. The overall context is incomplete for a mutation tool.
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 baseline is 3. The description does not add parameter-specific meaning beyond what the schema already provides (e.g., conditional fields for email/webhook/slack).
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 'Create a new alert channel' with explicit types (slack, email, or webhook), making the action and resource specific. It distinguishes this creation tool from sibling tools like list_recent_alerts and acknowledge_alert.
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?
The description implies usage (when you need to set up an alert channel) but does not explicitly state when to use this tool versus alternatives or any exclusions. No reference to sibling tools or conditions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It merely states the action without disclosing what 'dismiss' entails—whether it permanently deletes the alert, marks it as acknowledged, requires specific permissions, or is reversible. This is a significant transparency gap for a mutation tool.
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 single sentence with direct, front-loaded wording. Every word earns its place, making it highly concise and structured appropriately.
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 simple tool (one parameter, full schema coverage, no output schema), the description is minimally adequate. However, it lacks details about return behavior or side effects, which an output schema or more descriptive text could provide. Complete enough for a basic dismissal but not informative.
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?
Input schema covers 100% of the parameter (alert_key) with a description and example, so baseline is 3. The tool description adds no additional meaning beyond restating 'by its alert key', not improving semantic 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 action 'Dismiss' and the resource 'active alert' by 'alert key', which is specific and unambiguous. It distinguishes from siblings like create_alert and list_recent_alerts by focusing on dismissal.
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?
The description implies usage (dismissing active alerts when they need to be acknowledged) but does not explicitly state when to use this instead of other tools like list_recent_alerts or create_alert. No exclusions or alternatives are mentioned, making usage guidance implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior itself. 'Get' implies a read-only operation, and the description lists the returned data, which is helpful. However, it says nothing about error behavior, authentication requirements, rate limits, or whether any side effects occur, so some transparency gap remains.
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 single, tightly scoped sentence that conveys the tool's purpose, data returned, and parameter scope without fluff or repetition. Every word earns its place, and it is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one optional parameter, the description adequately covers the key aspects: what metrics are returned and how scope is controlled. The absence of an output schema is partially compensated by listing the metrics, though it does not describe the return format (e.g., object structure) or failure modes, which would improve completeness.
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?
The input schema already provides a full description for the single 'queue' parameter (100% coverage), including the behavior when omitted. The tool description adds no new parameter-specific meaning beyond the schema, so it does not elevate the baseline.
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's function with a specific verb ('Get') and resource ('queue status'), listing concrete metrics (queue depth, failed job count, oldest job age) and scope ('all queues or a specific queue'). This distinguishes it from sibling tools like get_cron_status or get_horizon_status, which target different resources.
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 given on when to choose this tool over alternatives, nor are any exclusions or prerequisites mentioned. The only usage nuance is the optional 'queue' parameter, which the schema also communicates. The description does not provide context to help an agent decide between this and sibling status tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. The verb 'list' suggests a read-only operation, and the time-window constraint is stated. However, it does not explicitly confirm that the tool has no side effects (e.g., does not acknowledge alerts) nor describe the return format, leaving some behavioral details opaque.
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 single, front-loaded sentence with no redundant information. Every word contributes meaning, and it is appropriately concise for a simple list operation.
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?
For a simple optional-parameter list tool, the description adequately conveys the core functionality, but it lacks coverage of return structure and side-effect guarantees. Given the absence of an output schema and annotations, the description could be more complete (e.g., mention read-only nature explicitly), but it is not severely underspecified.
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?
The input schema already provides full coverage of the single 'hours' parameter, including its meaning and default value. The tool description's reference to 'N hours' adds no additional semantic detail beyond the schema, so the baseline of 3 applies.
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 uses the specific verb 'list' with a clear resource ('alerts') and scope ('fired in the last N hours'), which unambiguously distinguishes it from sibling tools that target scheduled jobs or statuses. It clearly states what the tool does.
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?
The description implies when to use this tool (when you need to see alerts that have fired in a recent time window) but does not explicitly state when not to use it or mention alternatives like acknowledge_alert or the status tools. There is no comparison to siblings, so usage guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the burden of behavioral disclosure. The verb 'Get' implies a read-only operation, and specifying the return fields (status, exit code, duration) adds useful context. However, it does not explicitly state that the tool has no side effects, nor does it describe error conditions or behavior when the command is not found.
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 single sentence of fourteen words, front-loading the verb and result. Every word contributes meaning, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with no output schema, the description covers the essential purpose and return data. It could mention return formatting or edge cases, but the tool's simplicity and schema coverage make it adequately complete.
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?
The schema fully describes the single parameter, including an example and partial-match behavior. The description's phrase 'specific cron command' adds minimal semantic value beyond the schema, so the baseline of 3 applies.
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 uses the verb 'Get' and specifies the resource ('specific cron command') and the exact data returned ('last run status, exit code, and duration'). This clearly distinguishes it from sibling tools like get_queue_status or list_scheduled_jobs, which target different resources.
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?
The description implies usage for checking the status of a specific cron command, but it does not explicitly contrast with sibling tools or provide when-not-to-use guidance. For example, it doesn't mention that list_scheduled_jobs should be used to see all scheduled jobs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds concrete behavioral context by enumerating the returned data (supervisor states, paused status, failed jobs per minute), making clear it is a read-only snapshot. With no annotations, it does not explicitly state non-destructiveness or auth requirements, but the 'Get' verb implies a safe read operation. It covers the key behavior beyond the tool name.
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?
A single, front-loaded sentence with no redundant words. It immediately names the action and resource, then lists the relevant data points. Optimal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless read-only tool with no output schema, the description sufficiently communicates what the tool does and what it returns. The listed items give a clear picture, though it lacks explicit return format or error behavior. This is adequate for a simple health-check snapshot.
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?
The tool has zero parameters and an empty schema, so the description correctly adds no parameter-specific information. Per the rubric, zero parameters baseline is 4.
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 a specific verb ('Get') and resource ('Laravel Horizon health'), listing exact data points (supervisor states, paused status, failed jobs per minute). This distinguishes it from sibling tools like get_queue_status by focusing on Horizon specifically.
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. It does not mention sibling tools, exclusions, or specific scenarios. The word 'Horizon' implies a Laravel-specific context, but explicit usage instructions are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. The verb 'List' signals a read-only operation, and the content of results (last run status and timing) is disclosed. However, it doesn't explicitly state that no changes are made or that it provides a snapshot view, though that is largely inferable. Given the low-risk nature, this is adequate but not rich.
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?
A single, grammatically clear sentence with no fluff; the verb and object are front-loaded, making the purpose immediately apparent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple listing tool with no parameters and no output schema. The description tells the user what data will be returned (status and timing), which is sufficient for this level of complexity. It could note that it only covers 'monitored' cron commands, which is a constraint, but overall it's adequately complete.
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?
The tool has zero parameters, and the schema is empty. Per the baseline rule, a score of 4 is given since the description doesn't need to compensate for parameter documentation when there are none.
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 uses the specific verb 'List' and identifies the resource as 'monitored cron commands', clearly distinguishing it from sibling tools like get_cron_status (which likely targets a single job) by emphasizing the list scope.
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?
The description clearly implies this is for listing all monitored cron commands, but it does not explicitly contrast with alternatives like get_cron_status for per-job status, nor does it state when not to use it. This leaves usage guidance implicit rather than explicit.
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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