TypeScript MCP Server Boilerplate
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: calculator for math, greeting for salutations, and time for date/time retrieval. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool.
Naming Consistency5/5All tool names follow a consistent pattern of simple, descriptive nouns (calculator, greeting, time). While not using a verb_noun structure, the naming is uniform and predictable across the set, enhancing readability and coherence.
Tool Count2/5With only 3 tools, the set feels thin for a server labeled as a 'TypeScript MCP Server Boilerplate,' which implies a broader utility or foundational purpose. This minimal count suggests under-scoping, as typical boilerplates might include more varied or domain-specific tools.
Completeness2/5The tools cover unrelated, basic functions (math, greetings, time) without a clear domain, making it impossible to assess coverage meaningfully. There are significant gaps for any coherent purpose, as these tools do not form a complete surface for development, automation, or other typical boilerplate use cases.
Average 3/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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
- 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 only states what the tool does ('say hello or goodbye') without mentioning any behavioral traits like output format, side effects, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.
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 and front-loaded, consisting of a single, clear sentence that directly states the tool's purpose. There is no wasted language, making it efficient and easy to parse for an AI agent.
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 simplicity and lack of annotations or output schema, the description is incomplete. It doesn't cover behavioral aspects like what the output looks like or any constraints, which are necessary for proper tool invocation. This makes it inadequate for full contextual understanding.
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 adds no parameter semantics beyond what the input schema already provides. Since schema description coverage is 100%, the baseline score is 3. The description doesn't explain parameter interactions or provide additional context, so it meets the minimum but doesn't add extra value.
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 with specific verbs ('say hello or goodbye') and identifies the target ('to someone'), making it easy to understand. However, it doesn't differentiate this tool from potential siblings like 'calculator' or 'time', which serve entirely different purposes, so it's not a perfect 5.
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 any context, prerequisites, or exclusions, leaving the agent to infer usage based solely on the purpose statement. This lack of explicit guidelines reduces its helpfulness.
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 states the tool performs calculations but doesn't reveal any behavioral traits such as error handling (e.g., division by zero), precision limits, rate limits, or authentication needs. This leaves significant gaps in understanding how the tool behaves in practice.
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 with no wasted words. It's appropriately sized for a simple tool and front-loads the core purpose without unnecessary elaboration. Every word earns its place in conveying the tool's function.
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?
Given the tool's low complexity (basic calculations) and rich input schema (100% coverage), the description is minimally adequate. However, with no annotations and no output schema, it lacks context about behavioral traits and return values. The description doesn't compensate for these gaps, making it incomplete for fully informed tool selection.
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 input schema has 100% description coverage, with clear parameter descriptions and an enum for operations. The description adds no additional meaning beyond what the schema provides, such as explaining operation semantics or edge cases. However, with full schema coverage, the baseline score of 3 is appropriate as the schema adequately documents parameters.
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 'Perform basic mathematical calculations' clearly states the tool's function with a specific verb ('perform') and resource ('calculations'), distinguishing it from sibling tools like 'greeting' and 'time'. However, it doesn't specify what 'basic' means or differentiate from potential advanced calculation tools, keeping it from a perfect 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, limitations, or context for choosing this calculator over other methods. The agent must infer usage solely from the tool name and description.
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 the full burden of behavioral disclosure. It states what the tool does but lacks details on traits like rate limits, error handling, or default behaviors beyond what's implied. For example, it doesn't specify if the tool returns a string or structured data, or if there are any constraints on timezone inputs.
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 and front-loaded with a single, clear sentence that states the tool's purpose without any wasted words. It efficiently communicates the core functionality, making it easy to understand at a glance.
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?
Given the tool's low complexity (2 optional parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on output format or behavioral traits, which could be helpful for an agent. However, the simplicity of the tool means these gaps are less critical.
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 schema description coverage is 100%, with clear documentation for both parameters in the input schema. The description adds no additional meaning beyond the schema, such as explaining the implications of different formats or timezone choices. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
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 with a specific verb ('Get') and resource ('current date and time'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'calculator' or 'greeting', which is unnecessary here since the functionality is distinct by nature.
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. While the tool's purpose is straightforward, it doesn't mention any context or prerequisites for usage, such as when timezone adjustments might be needed or if there are limitations.
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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- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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