Skip to main content
Glama
Ruadgedy

filesystem

by Ruadgedy

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a single, clear purpose: reading, writing, or listing. There is no overlap between these operations, so an agent can easily select the correct tool.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: read_file, write_file, list_directory. This makes the API predictable and easy to remember.

    Tool Count3/5

    Three tools is a minimal set. While it covers basic file operations, a typical filesystem server would also include delete, rename, or move operations, making the count feel thin for the advertised scope.

    Completeness2/5

    The server lacks common filesystem operations such as delete, rename, move, and directory creation. This is a significant gap; for example, an agent cannot clean up or reorganize files after creating them.

  • Average 4.1/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 27 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
  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • 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 discloses the output format (FILE or DIR labeling) but does not specify behavior for edge cases like nonexistent paths, hidden files, or recursion. With no annotations, the description carries the transparency burden but only partially fulfills it.

    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 two sentences, front-loaded with the tool's purpose and supplemented with parameter details. It is concise with no redundancy.

    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?

    The tool has a single parameter and an output schema, and the description covers the core usage. However, it lacks details about error handling and listing scope (e.g., recursive), though the simplicity of the tool mitigates this gap.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description includes an Args section explaining that the 'path' parameter is a directory path relative to the workspace, defaulting to the workspace root. This adds semantic meaning absent from the input schema, which has no description and only a default of '.'.

    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 lists directory entries in the workspace and labels each entry as FILE or DIR, distinguishing it from sibling file read/write tools.

    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 over read_file or write_file, nor any prerequisites or exclusions. The description only covers basic usage with the path argument.

    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 are provided, so the description must carry the behavioral burden. It adds useful context about the path being relative to the workspace, but does not disclose error handling, file encoding, or side effects. Since this is a read-only operation, the absence of mutation details is acceptable, but the lack of error/edge-case info leaves a gap.

    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, with a single-purpose sentence and a brief parameter explanation. It is front-loaded with the action and contains no unnecessary words or repetition.

    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 simple read tool with one parameter and an output schema, the description covers the essential context: what is read, from where, and how to specify the path. It lacks details on failure modes, but the presence of an output schema reduces the burden of explaining return behavior. Overall, it is sufficiently complete for the tool's simplicity.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 0%, but the description fully compensates by explaining the 'path' parameter with a clear definition (relative to workspace) and examples. This adds significant meaning beyond the schema's bare 'Path' property, making the parameter semantics very clear.

    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 uses a specific verb ('读取' meaning read) and resource ('workspace 内某个文本文件' meaning text file in the workspace), clearly distinguishing it from siblings like write_file and list_directory. It states the function is to read content and return it, which is unambiguous.

    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 usage by stating it reads files from the workspace, but it does not explicitly mention when to use this tool versus alternatives. No exclusions or alternative tool names are provided, though the sibling names (write_file, list_directory) make the context somewhat clear.

    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 key behavioral traits: automatic creation of missing files/parent directories, and full overwriting of existing content. Since no annotations are provided, these details are crucial and are adequately covered. It also constrains the path to be workspace-relative.

    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 concise, consisting of a one-sentence overview plus brief parameter explanations. No redundant information is present; every sentence is informative.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's simplicity, the description adequately covers the core behavior: writing content, handling missing paths, and overwriting semantics. The presence of an output schema means return values are already specified externally, so no additional return-value detail is needed.

    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?

    With 0% schema description coverage, the description compensates by explaining both parameters: path is relative to workspace, and content is the text to write (overwriting existing). This provides essential meaning beyond the bare schema types.

    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: writing text content into a workspace file, with specific mention of auto-creating missing paths and overwriting existing content. This distinguishes it from sibling tools like read_file and list_directory.

    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 does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions (e.g., when not to use). While the tool's function is implied, there is no direct guidance on choosing it over read_file or list_directory, though the context is clear.

    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-test MCP server

Copy to your README.md:

Score Badge

mcp-test 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/Ruadgedy/mcp-test'

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