Skip to main content
Glama
jmpijll

unraid-code-mode-mcp

by jmpijll
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0-beta.3

  • Disambiguation5/5

    The two tools have clearly distinct purposes: 'execute' runs GraphQL operations, while 'search' explores the schema. There is no overlap, and their descriptions unambiguously differentiate them.

    Naming Consistency4/5

    Both tool names are single, lowercase verbs that directly describe their function. Although they lack a verb_noun pattern, they follow a consistent, simple style that is easy to understand.

    Tool Count5/5

    With only 2 tools, each covers a fundamental aspect of interacting with a GraphQL API: discovery and execution. The count is perfectly scoped for the server's purpose, avoiding unnecessary complexity.

    Completeness5/5

    The server provides all necessary functionality: you can explore the schema with 'search' and then execute any discovered operation with 'execute'. There are no obvious gaps in coverage.

  • Average 4.6/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 13 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • 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

  • Behavior4/5

    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. It explicitly states the sandbox is read-only and has no network, which are critical traits. It also describes the sandbox environment, available globals, and that console.log output is captured. This provides sufficient transparency, though it could mention response format or error behavior.

    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 well-structured with sections for globals, functions, and examples. Every sentence adds value. However, it is somewhat verbose; the examples and function lists could be slightly condensed without losing clarity. Still, the structure aids comprehension.

    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 complexity (JavaScript execution in a sandbox with multiple globals and no output schema), the description is remarkably complete. It covers the environment, all available functions with their purpose, input/output shapes, and concrete examples. An agent could immediately use the tool correctly based on this description alone.

    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 input schema has one parameter 'code' with a minimal description. The tool's description compensates extensively by detailing the global functions and variables available (e.g., searchOperations, getOperation, getType), their signatures, and usage examples. This adds immense meaning beyond the schema, effectively teaching the agent how to construct the JavaScript code.

    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 'Search the Unraid GraphQL schema by writing JavaScript.' It specifies the resource and action, and distinguishes from sibling 'execute' by positioning this as a discovery tool before invocation. The verb 'search' and resource 'Unraid GraphQL schema' are specific and unambiguous.

    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 provides clear context: use this tool to discover what to call before invoking 'execute', and notes the sandbox is read-only with no network. It does not explicitly state when not to use it, but the sibling relationship and discovery purpose imply that. The examples further guide usage, making it nearly complete.

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

  • Behavior5/5

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

    With no annotations provided, the description fully discloses behavioral traits: async execution, sandbox memory/time bounds, credential isolation, and API call limits leading to errors. It also explains return value structures, leaving little ambiguity about the tool's behavior.

    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 well-structured with clear sections (overview, methods, examples, limits) and front-loads the purpose. While each section contributes value, the examples are somewhat lengthy, and the overall length could be trimmed slightly without losing clarity.

    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 no output schema, the description covers return types, error conditions, limits, and provides multiple examples. It sufficiently equips an agent to use the tool correctly, lacking only explicit comparison to siblings but otherwise complete.

    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 single parameter 'code' has a basic schema description, but the tool description adds immense value by detailing how to write the JavaScript, available methods, and examples. This significantly enhances the agent's understanding beyond the schema alone.

    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's purpose as executing JavaScript to run Unraid GraphQL operations using the `unraid.local` namespace. It differentiates from the sibling 'search' by implying a code execution context rather than a simple search, and provides specific methods and examples.

    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 offers extensive guidance on internal usage: async/await, typed vs raw calls, examples, and limits. However, it does not explicitly contrast with the sibling tool 'search' or state when to use this tool versus that alternative, which would improve cross-tool decision-making.

    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

unraid-code-mode-mcp MCP server

Copy to your README.md:

Score Badge

unraid-code-mode-mcp 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/jmpijll/unraid-code-mode-mcp'

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