system-mcp

by Chandukasireddy

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct system component (battery, CPU, disk, GPU, memory, network, processes, and overview) with no functional overlap.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern with descriptive suffixes like _metrics, _tasks, _overview.
Tool Count5/5
8 tools is well-scoped for a system monitoring server, covering major resources without being excessive or too sparse.
Completeness4/5
Core system metrics are covered, but lacks deeper details like per-interface network stats or sensor data, which are minor gaps.
Average 3.7/5 across 8 of 8 tools scored. Lowest: 2.8/5.
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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states 'Get detailed CPU metrics,' implying a read-only operation but failing to mention any constraints, side effects, or specifics like sampling behavior, rate limits, or data format. The description lacks transparency beyond the basic verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, making it concise. However, it is under-specified to the point of being minimally informative. It earns its place but does not add enough detail to justify its brevity. A 3 reflects that it is not verbose but lacks substance.
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, a simple parameter, and the existence of an output schema, the description should at least enumerate the types of CPU metrics returned (e.g., usage, temperature, load). It fails to do so, leaving the agent to guess the exact output. The tool is simple, but the description is incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter (sample_seconds) with 0% schema description coverage. The tool description does not mention this parameter or explain its meaning or effect. While the parameter name is somewhat self-explanatory, the description adds no value beyond the schema's property definition, leaving the agent uninformed about how sample_seconds affects results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get detailed CPU metrics' clearly states the verb ('Get') and resource ('CPU metrics'), distinguishing it from sibling tools like battery_metrics or disk_metrics. While 'detailed' is vague, the tool's name and the sibling set make its purpose evident.
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 provides no explicit guidance on when to use this tool versus alternatives. However, the sibling tool names (e.g., battery_metrics, disk_metrics) imply that cpu_metrics is for CPU-specific data, giving implicit context. No when-not-to-use or alternative comparisons are 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 provided, so the description must cover behavioral traits. It only indicates a read operation but lacks details on side effects, permissions, or performance implications.
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 a single, focused sentence with no wasted words. It is appropriately brief but could benefit from slight expansion.
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?
The tool has low complexity and an output schema, so the description need not explain return values. However, it lacks usage guidance and behavioral details, making it only minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It mentions the 'path' parameter and a default, but does not clarify valid values, expected format, or behavior if the path is invalid.
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 retrieves disk usage and IO counters for a given path, with a specific verb and resource that distinguishes it from sibling tools like cpu_metrics or memory_metrics.
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 on when to use this tool versus other metrics tools, nor any conditions or prerequisites. The description simply defines the function without 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, the description carries full burden for behavioral transparency. It does not disclose whether the operation is safe (read-only), whether it requires permissions, or what the output structure is (though an output schema exists). The sorting behavior is implied but not detailed.
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 core functionality. Every part is informative and there is no redundancy. Appropriate length for the tool's simplicity.
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 tool has only two simple parameters and an output schema, the description covers the essential purpose but lacks details like valid sort_by values, limit bounds, and nature of 'top' (e.g., current snapshot). Adequate but could be more 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?
Schema coverage is 0%, so the description must add parameter meaning. It explains sort_by can be 'CPU or memory' but does not specify valid values (e.g., 'cpu', 'memory') or constraints. Limit parameter is not mentioned beyond default. Partially compensates but incomplete.
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 (Get), the resource (top running tasks/processes), and the sorting criterion (by CPU or memory). It effectively distinguishes from sibling metrics tools like battery_metrics or cpu_metrics, which focus on system-level metrics rather than process listing.
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. While siblings are different in nature, the description does not mention that this tool is for process-level information, nor does it advise against using it for system metrics. Lacks explicit when-to-use or when-not-to-use 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?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states 'Get RAM and swap usage details', which is minimal. It does not mention whether the operation is read-only, any permissions needed, rate limits, or what happens under error conditions. The output schema may define return values, but the description adds no behavioral context beyond the basic purpose.
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 short sentence, 'Get RAM and swap usage details.' It is concise, front-loaded, and contains no unnecessary words. Every word earns its place.
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?
Given the tool is simple with no parameters and an output schema likely defining the return structure, the description is mostly complete. However, it could be slightly more specific about what 'details' entails (e.g., used, free, percentages). The presence of sibling tools covering other metrics provides context for the overall system monitoring domain.
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 input schema is fully documented (100% coverage). The description adds no parameter information, which is appropriate since there are none. According to guidelines, 0 parameters yields a baseline of 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 'Get RAM and swap usage details', specifying the verb (Get) and resource (RAM and swap). This distinguishes it from sibling tools like cpu_metrics or disk_metrics, which cover different system 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?
No guidance on when to use this tool vs alternatives. The description is self-explanatory for its intended use, but lacks explicit context about when not to use it or potential alternatives among sibling 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?
The description indicates a read operation, which is consistent with a non-destructive tool. However, it does not elaborate on data freshness, error handling, or permission requirements. Since there are no annotations, a bit more context would improve 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 a single, clear sentence that immediately conveys the tool's purpose with no wasted words. It is optimal for a simple tool with no inputs.
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?
Given zero parameters and the existence of an output schema, the description covers the main aspects. It could be slightly improved by specifying that the data represents a current snapshot, but overall it is largely 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?
No parameters exist, so the description cannot add parameter semantics. The description appropriately focuses on the output, which is consistent with the baseline score of 4 for tools with zero parameters.
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 'Get' and specifies three data points (battery status, charge level, charging state), effectively distinguishing it from sibling tools like cpu_metrics or disk_metrics.
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?
No explicit guidance on when to use or not use this tool. The implied context is that it is for battery-related queries, but no alternatives or exclusions are mentioned.
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?
No annotations exist, so the description must disclose behavioral traits. It describes a read operation ('get') without side effects, which is minimal but does not elaborate on permissions, rate limits, or potential impacts. Adequate for a simple metrics 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 no wasted words. It is concise and front-loaded with the action and subject.
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?
Given the tool's simplicity (no parameters, output schema exists), the description adequately states what it returns (counters and connection count). It lacks additional context like snapshot vs streaming, but this is not critical.
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?
There are no parameters; schema coverage is 100% trivially. Baseline for zero parameters is 4. The description adds no parameter details because none exist, which is appropriate.
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 retrieves 'system network traffic counters and active connection count,' specifying the resource (network metrics) and the action (get). This distinguishes it from sibling tools like cpu_metrics or memory_metrics.
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?
No explicit guidance on when to use vs alternatives is provided. However, the name and description imply usage for network-related metrics, and sibling names suggest differentiated system domains. This is adequate but not 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 carries full burden. It correctly implies a read-only operation and lists returned elements, but lacks details on performance, side effects, or response structure.
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 that delivers key information without filler. Every word earns its place.
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?
Given the tool's simplicity and presence of an output schema, the description covers the essential components. It could mention that only selected system aspects are included, but overall it is sufficient.
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?
No parameters exist, so the baseline is 4. The description adds no parameter info, but none is needed.
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 verb 'Get' and the resource 'overall system summary', listing components (OS, CPU, RAM, disk, battery, process count). It effectively distinguishes from sibling tools like cpu_metrics or battery_metrics by emphasizing the broad overview.
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 use for a general summary but does not explicitly state when to choose this over individual metric tools. No when-not or alternative guidance is provided.
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 discloses a key behavioral trait: reliance on nvidia-smi, implying unavailability on non-NVIDIA systems. With no annotations provided, this is valuable transparency. However, it does not clarify the exact behavior when GPU info is not available (e.g., returns null vs raise error).
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 core purpose ('Get GPU information') and effectively communicates the key condition. No wasted words.
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 zero-parameter tool with an output schema, the description adequately conveys the main purpose and an important caveat (nvidia-smi dependency). It could be slightly more complete by stating the outcome when GPU info is unavailable, but overall it is sufficiently informative.
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 no parameters, and the input schema is fully documented (100% coverage). The description does not need to add parameter meaning, so the baseline of 4 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 clearly states the tool gets GPU information, specifies it is availability-dependent (if available), and identifies the source (nvidia-smi). This distinguishes it from sibling tools like cpu_metrics or memory_metrics.
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 that this tool is for GPU-specific metrics, and sibling names suggest alternative tools for other metrics. However, it lacks explicit guidance on when to use this tool versus alternatives, such as conditions under which GPU info might be unavailable.
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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