Skip to main content
Glama
spences10
by spences10

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: confirm_command handles safety checks, execute_command runs commands, get_directory_info lists files, get_disk_usage shows storage, get_environment retrieves variables, get_system_info provides system details, and list_processes shows running processes. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with snake_case (e.g., confirm_command, execute_command, get_directory_info). The naming is uniform throughout, using 'get_' for retrieval operations and clear action-object pairs.

    Tool Count5/5

    With 7 tools, the server is well-scoped for WSL execution and system monitoring. Each tool serves a specific and necessary function, covering command execution, file management, system diagnostics, and process handling without being overly sparse or bloated.

    Completeness4/5

    The toolset provides strong coverage for WSL operations, including command execution, file system inspection, system monitoring, and environment management. A minor gap exists in file manipulation (e.g., create/delete files) or network-related tools, but core workflows are well-supported.

  • Average 2.6/5 across 7 of 7 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 1 of 1 community issues answered or closed in the last 6 months
    • 5 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
  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    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.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    The description adds no behavioral information beyond what the readOnlyHint annotation already provides. While the annotation correctly indicates this is a read-only operation, the description doesn't disclose any additional behavioral traits such as what happens with invalid paths, whether it follows symlinks, what format the output takes, or any rate limits. With annotations covering the safety profile, this meets the baseline but adds minimal value.

    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 extremely concise at just four words with no wasted language. While this conciseness comes at the expense of completeness, every word directly relates to the tool's function. The structure is front-loaded with the core purpose, though there's no additional information to structure beyond this basic statement.

    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 the tool has readOnlyHint annotation but no output schema, the description should provide more context about what information is returned. The description doesn't explain what 'contents and info' includes, whether it returns file lists, metadata, permissions, or other directory attributes. For a tool with two parameters and no output schema, this leaves significant gaps in understanding what the tool actually produces.

    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?

    With 100% schema description coverage, the input schema already fully documents both parameters (path and details). The description adds no additional meaning about what 'directory contents and info' specifically entails, how the boolean 'details' parameter affects the output, or what constitutes a valid path format. The baseline score of 3 reflects adequate schema coverage without description enhancement.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tautological: description restates name/title.

    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 provides no guidance on when to use this tool versus alternatives. With siblings like 'get_disk_usage' and 'get_system_info' that might overlap in system information retrieval, there's no indication of when directory-specific information is needed, what prerequisites exist, or when other tools might be more appropriate. This leaves the agent without context for tool selection.

    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 annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description doesn't contradict this (it uses 'get' which aligns with read-only). However, the description adds no behavioral context beyond what annotations provide—it doesn't mention what specific disk metrics are returned, whether it requires special permissions, if there are rate limits, or how it handles errors. With annotations covering safety, a baseline 3 is appropriate as the description adds minimal value.

    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 extremely concise—a single phrase with zero wasted words. It's front-loaded with the core purpose, though this brevity comes at the cost of detail. Every word earns its place, making it efficient for quick scanning.

    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 the tool's simplicity (1 optional parameter, read-only annotation, no output schema), the description is incomplete. It doesn't explain what disk information is returned (e.g., free space, total space, usage percentage), how to interpret results, or default behavior if 'path' is omitted. With no output schema, the description should compensate by outlining return values, but it fails to do so.

    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 1 parameter with 100% description coverage ('Path to check'), so the schema fully documents the parameter. The description adds no meaning beyond what the schema provides—it doesn't explain what 'path' means in context (e.g., filesystem path, default behavior if omitted), nor does it provide examples or constraints. Baseline 3 is correct when schema coverage is high.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tautological: description restates name/title.

    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 provides no guidance on when to use this tool versus alternatives. There are no explicit when/when-not instructions, no mention of prerequisites, and no reference to sibling tools like 'get_directory_info' or 'get_system_info' that might offer overlapping functionality. The agent receives no usage context beyond the tool name.

    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 annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description doesn't add any behavioral context beyond what the annotations provide - no information about what specifically gets retrieved, how the filtering works, whether there are rate limits, or what the output format looks like. However, it doesn't contradict the annotations, so it earns a baseline score for not creating confusion while adding minimal value.

    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 extremely concise at just three words. While it's arguably too brief for adequate tool documentation, it contains zero wasted words and is perfectly front-loaded with the core purpose. Every word earns its place, making this maximally efficient in terms of word economy.

    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?

    For a tool with no output schema and only basic annotations, the description is incomplete. It doesn't explain what format the environment variables are returned in, whether it retrieves all variables or a subset, or how the filtering parameter interacts with the retrieval. While the schema covers the single parameter, the overall context for using this tool effectively is insufficient given the complexity of environment variable retrieval.

    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 'filter' parameter clearly documented as 'Filter pattern (grep)'. The description itself provides no additional parameter information. With complete schema coverage, the baseline score of 3 is appropriate since the schema does all the parameter documentation work and the description doesn't need to compensate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tautological: description restates name/title.

    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 provides absolutely no guidance about when to use this tool versus alternatives. There's no mention of when this tool is appropriate, when other tools might be better suited, or any prerequisites for its use. Given that there are multiple 'get_' sibling tools that retrieve different types of system information, this lack of differentiation guidance is a significant gap.

    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?

    Annotations indicate destructiveHint=true and readOnlyHint=false, which the description doesn't contradict. However, the description adds minimal behavioral context beyond annotations—it doesn't explain what makes commands destructive, potential side effects, or execution constraints like permissions or rate limits. The 'use read-only tools when possible' hint adds some caution but lacks specificity.

    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 very brief—a single sentence with a parenthetical note. It's front-loaded with the core purpose, but the parenthetical feels tacked on and doesn't integrate smoothly. While concise, it could be more structured to separate purpose from guidance.

    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 the destructive nature (per annotations) and lack of output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or safety considerations, leaving gaps for a mutation tool with potential side effects. The context signals don't compensate for these omissions.

    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?

    With 100% schema description coverage, the input schema fully documents all three parameters. The description adds no parameter-specific information beyond what's in the schema, so it meets the baseline of 3 without compensating or adding value.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tautological: description restates name/title.

    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?

    The description provides no guidance on when to use this tool versus alternatives. While it mentions 'use read-only tools when possible,' this is vague advice that doesn't specify concrete alternatives or scenarios where this tool should be preferred or avoided compared to siblings like get_directory_info or list_processes.

    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?

    Annotations already declare destructiveHint=true and readOnlyHint=false, so the agent knows this is a destructive write operation. The description adds the 'dangerous' qualifier which reinforces the destructive nature, but doesn't provide additional behavioral context like what happens after confirmation, whether confirmation is reversible, or what specific dangers are involved. The description aligns with but doesn't significantly expand beyond the annotations.

    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 extremely concise at just three words, with zero wasted language. It's front-loaded with the core concept and doesn't contain any unnecessary elaboration. For a simple confirmation tool, this brevity is appropriate.

    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?

    For a destructive tool with no output schema, the description is inadequate. It doesn't explain what happens after confirmation, what gets executed, how to obtain the confirmation_id, or what the dangerous command actually is. Given the destructive nature and workflow context implied by the tool name, more guidance about the confirmation process and its consequences is needed.

    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 schema already documents both parameters (confirmation_id and confirm) with their types and basic descriptions. The description doesn't add any meaning about what a confirmation_id represents, how it's obtained, or the implications of setting confirm to true versus false. Baseline 3 is appropriate when the schema provides complete parameter documentation.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tautological: description restates name/title.

    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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, when this confirmation step is required, or how it relates to sibling tools like 'execute_command'. There's no indication of workflow context or sequencing with other 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 annotations include readOnlyHint: true, indicating this is a safe read operation. The description doesn't contradict this, as 'Get' aligns with read-only behavior. However, it adds no behavioral context beyond what annotations provide—such as what specific information is returned, potential rate limits, or authentication needs. With annotations covering the safety profile, the description adds minimal value, meeting the baseline for this dimension.

    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 extremely concise—a single phrase with no wasted words. It's front-loaded and to the point, which is efficient for a simple tool. However, it's arguably too concise, bordering on under-specification, as it sacrifices clarity for brevity. This earns a high score for conciseness but not a perfect 5 due to the trade-off with completeness.

    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 the tool's simplicity (0 parameters, read-only annotations) and lack of an output schema, the description is incomplete. It doesn't explain what 'system information' entails (e.g., WSL version, distribution details, or hardware info), leaving the agent uncertain about the return values. With no output schema, the description should provide more context on the expected data, but it fails to do so, making it inadequate for full understanding.

    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 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to compensate for any gaps, as the schema fully handles the lack of inputs. This justifies a baseline score of 4, as the description isn't required to add parameter semantics in this case.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tautological: description restates name/title.

    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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't specify what type of system information it retrieves (e.g., OS details, version, configuration) compared to siblings like get_disk_usage or list_processes, leaving the agent to guess based on the tool name alone. There are no explicit instructions on context or exclusions, resulting in poor usage guidance.

    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 adds minimal behavioral context beyond the annotations. The annotation 'readOnlyHint: true' already indicates this is a safe read operation. The description implies it lists processes but doesn't disclose details like output format, pagination, or performance characteristics. It doesn't contradict annotations, but offers little additional value.

    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 extremely concise—a single sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality, making it efficient for quick comprehension. Every word earns its place, adhering to best practices for brevity.

    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's low complexity (one optional parameter) and the presence of annotations covering safety, the description is minimally adequate. However, without an output schema, it doesn't explain what the tool returns (e.g., process list format), leaving a gap in completeness. It relies heavily on structured data for context.

    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?

    With 100% schema description coverage, the input schema fully documents the optional 'filter' parameter. The description doesn't add any parameter semantics beyond what the schema provides, such as examples of filter usage or format. This meets the baseline for high schema coverage but doesn't enhance understanding.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tautological: description restates name/title.

    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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios where this is preferred over sibling tools like 'get_system_info' or 'execute_command', nor does it specify prerequisites or exclusions. This lack of context could lead to incorrect tool selection by an AI agent.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

mcp-wsl-exec MCP server

Copy to your README.md:

Score Badge

mcp-wsl-exec MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/spences10/mcp-wsl-exec'

If you have feedback or need assistance with the MCP directory API, please join our Discord server