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stevennevins

MCP Server Template

by stevennevins
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools, as there are no other tools to compare it against. The single tool's purpose is clearly defined, eliminating any ambiguity in tool selection.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect—there are no other tools to create inconsistency. The tool name 'example-tool' follows a simple, clear pattern without any conflicting conventions to evaluate.

    Tool Count2/5

    A single tool is generally too few for a server's purpose, as it limits functionality and suggests an incomplete or trivial implementation. For a server named 'MCP Server Template', one tool feels insufficient to demonstrate a coherent set of capabilities, making it borderline inadequate.

    Completeness1/5

    The server's purpose is unclear from the name 'MCP Server Template', but with only one generic tool ('example-tool'), there are significant gaps in coverage. It lacks any CRUD operations, lifecycle management, or domain-specific functions, making it severely incomplete for any practical application.

  • Average 2.6/5 across 1 of 1 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

  • This repository is licensed under ISC 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

  • Behavior2/5

    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. It states the tool 'processes input data', which implies some action but doesn't reveal behavioral traits like whether it's read-only, destructive, requires authentication, has side effects, or rate limits. This leaves significant gaps in understanding how the tool behaves.

    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, efficient sentence with no wasted words, making it appropriately concise. However, it's front-loaded with the basic purpose but lacks structure or additional details that could enhance clarity, keeping it simple but under-specified.

    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 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain what 'processes' means, the expected output, or behavioral context, leaving the agent with insufficient information to use the tool effectively despite the straightforward schema.

    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 description adds no specific meaning about the 'input' parameter beyond what the schema provides, which has 100% coverage and describes it as 'Input string to process'. With high schema coverage, the baseline is 3, as the schema adequately documents the parameter, and the description doesn't compensate or add further semantics.

    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 input data', which provides a basic purpose but is vague about what 'processes' entails. It doesn't specify the type of processing or outcome, and with no sibling tools, differentiation isn't needed. This is a minimal viable description that communicates a general function without specifics.

    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 offers no guidance on when to use this tool, such as context, prerequisites, or alternatives. With no sibling tools, it doesn't need to distinguish from others, but it lacks any usage instructions or scenarios, leaving the agent without direction on appropriate application.

    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.

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