Datetime MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: add-note handles note creation, format-date processes date formatting, and get-current-time retrieves current time. The descriptions are specific and unambiguous, making tool selection straightforward for an agent.
Naming Consistency2/5The naming is inconsistent with mixed conventions: add-note uses kebab-case, format-date uses kebab-case, and get-current-time uses kebab-case but has a longer name. While all are kebab-case, the verb styles vary (add, format, get), and the lack of a uniform pattern (e.g., all starting with 'get_' or using consistent verb forms) reduces predictability.
Tool Count3/5With only 3 tools, the count feels thin for a 'Datetime MCP Server' as it suggests limited functionality. While the tools cover basic datetime operations, the server's name implies a broader scope that might include more operations like date parsing, timezone handling, or interval calculations, making this borderline appropriate.
Completeness2/5The tool surface has significant gaps for a datetime server: it lacks core operations such as parsing dates, calculating differences between dates, handling timezones, or converting between formats. The existing tools (add-note, format-date, get-current-time) do not provide a complete CRUD/lifecycle coverage for datetime manipulation, leading to potential agent failures in common scenarios.
Average 2.8/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No issues in the last 6 months
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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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Add a new note' implies a write operation, but it doesn't disclose any behavioral traits such as permissions required, whether the note is saved permanently, if there are rate limits, or what happens on success/failure. This is a significant gap for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with 'Add a new note'—a single, front-loaded sentence that wastes no words. It efficiently conveys the core action without unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a write operation with 2 parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't provide enough context for an AI agent to use the tool effectively, missing details on behavior, parameters, and outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning parameters 'name' and 'content' are undocumented in the schema. The description adds no meaning beyond the schema—it doesn't explain what 'name' and 'content' represent, their formats, or constraints. This fails to compensate for the low coverage, leaving parameters poorly understood.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add a new note' clearly states the action (add) and resource (note), making the basic purpose understandable. However, it doesn't specify what kind of note (e.g., text note, annotation, comment) or distinguish it from potential sibling tools (though the actual siblings are unrelated time/date tools). This leaves the purpose somewhat vague but adequate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., adding notes to what system or entity), or exclusions. With sibling tools being unrelated (format-date, get-current-time), there's no explicit comparison, leaving usage unclear.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't cover important aspects like error handling, input validation, timezone considerations, or output format details. This is inadequate for a tool with potential complexity in date parsing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without any wasted words. It's appropriately sized for this simple tool and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a date formatting tool with no annotations and no output schema, the description is insufficient. It doesn't explain what format strings are supported, how date strings should be formatted, what happens with invalid inputs, or what the output looks like. The agent would need to guess about important behavioral aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('format') and resource ('date string'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get-current-time' which might also handle date/time operations, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. The description doesn't mention sibling tools or contexts where this formatting operation is appropriate, leaving the agent without usage context.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns time 'in various formats' but doesn't specify what those formats are, whether the operation is read-only, if there are rate limits, or how errors are handled. This leaves significant behavioral aspects unclear for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool and front-loads the core functionality, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects like error handling or return formats, which would help the agent use it correctly despite the absence of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'various formats', which aligns with the 'format' parameter's enum values in the schema. However, with 100% schema description coverage, the schema already documents both parameters thoroughly. The description adds minimal value beyond what the structured schema provides, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose ('Get the current time') and specifies the scope ('in various formats'), which distinguishes it from potential time-related operations. However, it doesn't explicitly differentiate from sibling tools like 'format-date', which might handle date formatting rather than current time retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'format-date'. It doesn't mention prerequisites, limitations, or scenarios where this tool is preferred, leaving the agent to infer usage from the tool name alone.
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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