MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tools have distinct names like api-client, data-processor, and file-handler, which suggest different purposes, but descriptions are generic (e.g., 'ApiClient tool description'), leaving some ambiguity about their specific functions. Without detailed descriptions, it's unclear if there's overlap in processing or handling tasks.
Naming Consistency2/5
Naming is inconsistent with mixed conventions: hyphen-case (api-client, data-processor, my-tool), snake_case (example_tool), and camelCase (FileHandler). This lack of a predictable pattern makes the tool set harder to navigate and could confuse agents.
Tool Count4/5
With 5 tools, the count is reasonable for a general-purpose MCP server, suggesting a moderate scope. It's not too thin or heavy, though the generic nature of the tools makes it hard to assess if this number fits a specific domain perfectly.
Completeness2/5
Given the generic tool names and descriptions, it's impossible to infer a clear domain, making completeness assessment difficult. However, the set lacks obvious CRUD or lifecycle coverage, and tools like 'example_tool' and 'my-tool' seem vague, indicating significant gaps for any specific workflow.
Average 1.7/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers none. It does not indicate whether this is a read or write operation, what permissions might be required, potential side effects, rate limits, or any other behavioral traits. The description is completely inadequate for a tool with unknown behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is brief, this is due to under-specification rather than effective conciseness. The single phrase 'ApiClient tool description' fails to convey necessary information and does not earn its place as a helpful description. It lacks any structure or front-loading of critical details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is severely incomplete. It does not explain what the tool does, when to use it, its behavior, or what it returns. For a tool with one parameter and unknown functionality, this description provides almost no useful context for an AI agent.
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% (the 'message' parameter is documented in the schema), so the baseline score is 3. The description adds no additional meaning about parameters beyond what the schema already provides, such as clarifying the purpose of the 'message' parameter or how it influences tool behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'ApiClient tool description' is a tautology that merely restates the tool name 'api-client' with minimal variation. It provides no specific verb or resource information, fails to distinguish this tool from its siblings (data-processor, example_tool, file-handler, my-tool), and gives no indication of what the tool actually does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. There is no mention of appropriate contexts, prerequisites, or comparisons to sibling tools, leaving the agent with no information to make an informed selection decision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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. However, it reveals nothing about the tool's behavior—such as whether it's read-only or destructive, its authentication needs, rate limits, or output characteristics. This is inadequate for a tool with unknown behavioral traits, especially without an output schema to clarify results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise, the description is under-specified rather than efficiently informative. 'DataProcessor tool description' is a placeholder-like phrase that fails to convey essential details, making it ineffective despite its brevity. Conciseness should not come at the cost of clarity, and this description does not earn its place with useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is severely incomplete. It does not explain what the tool does, when to use it, behavioral traits, or output expectations. For a tool named 'data-processor' with one parameter, this minimal description leaves critical gaps, making it inadequate for an AI agent to understand and invoke the tool correctly.
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 has 100% description coverage, with the 'message' parameter documented as 'Message to process'. The description adds no additional meaning beyond this, but the schema provides sufficient baseline information. With high schema coverage and only one parameter, a score of 3 reflects adequate but minimal parameter semantics from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'DataProcessor tool description' is a tautology that merely restates the tool name with minimal elaboration. It fails to specify what the tool actually does (e.g., what 'process' entails), what resource it operates on, or how it differs from sibling tools like 'file-handler' or 'api-client'. This provides no meaningful guidance for an AI agent to understand the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, nor does it reference sibling tools like 'file-handler' or 'api-client' that might handle related tasks. This leaves the agent with no information to make an informed selection among available tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. However, it gives no information about what the tool does (e.g., whether it's read-only, destructive, requires authentication, has rate limits, or returns specific outputs). The description is essentially empty, failing to meet even the minimal burden for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is brief, it is under-specified rather than concise. 'FileHandler tool description' is a placeholder that fails to convey essential information, making it inefficient. A truly concise description would front-load key details like purpose or usage, but this text lacks any substantive content to structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is severely incomplete. It does not explain what the tool does, how it behaves, or what it returns, leaving critical gaps for an AI agent. For a tool named 'file-handler' with siblings like 'data-processor', more context is needed to understand its role and functionality.
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 has 100% description coverage, with the single parameter 'message' documented as 'Message to process'. The description adds no additional meaning beyond this, such as explaining what 'process' entails or providing examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the schema already handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'FileHandler tool description' is a tautology that merely restates the tool name with minimal elaboration. It fails to specify what the tool actually does (e.g., read, write, delete, or manipulate files), what resources it operates on, or how it differs from sibling tools like 'data-processor' or 'api-client'. This provides no actionable information for an AI agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention any specific contexts, prerequisites, or exclusions, nor does it reference sibling tools like 'data-processor' or 'api-client' that might handle related tasks. This leaves the agent with no basis for selecting this tool appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description 'MyTool tool description' reveals nothing about whether this is a read/write operation, its side effects, authentication needs, rate limits, or response format. It fails to provide any behavioral context beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While concise with only three words, this is under-specification rather than effective brevity. The description fails to convey meaningful information and wastes the opportunity to guide the agent. Every sentence should earn its place, but here there are no substantive sentences to evaluate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a single parameter with full schema coverage, the description is completely inadequate. It doesn't explain what the tool does, when to use it, or what behavior to expect, leaving the agent with insufficient context to understand or invoke the tool effectively.
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 has 100% description coverage (the 'message' parameter is documented as 'Message to process'), so the baseline score is 3. The tool description adds no additional parameter information beyond what the schema already provides, such as format examples or constraints, but doesn't need to compensate for gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'MyTool tool description' is a tautology that merely restates the tool name with the word 'tool' added. It provides no information about what the tool actually does, what resource it operates on, or what specific action it performs. This fails to distinguish it from any sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives like 'api-client', 'data-processor', 'example_tool', or 'file-handler'. There is no mention of appropriate contexts, prerequisites, or exclusions. The agent receives zero usage direction.
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 burden. It states the tool 'processes messages' but does not disclose behavioral traits such as whether it's read-only or destructive, permission requirements, rate limits, or response format. This is inadequate for a tool with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is appropriately sized and front-loaded, clearly stating the tool's basic function without unnecessary elaboration.
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?
Given no annotations, no output schema, and a vague description, the description is incomplete. It fails to provide sufficient context for the agent to understand the tool's behavior, output, or how it fits with sibling tools, leaving 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%, with the parameter 'message' documented in the schema. The description adds no meaning beyond the schema, as it does not explain what 'processes' entails for the message parameter. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'processes messages', which provides a basic purpose but is vague about what 'processes' entails. It distinguishes from siblings like 'api-client' or 'file-handler' by focusing on messages, but lacks specificity about the type of processing or resources involved.
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. The description does not mention context, exclusions, or comparisons to sibling tools like 'data-processor' or 'my-tool', leaving the agent without usage direction.
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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