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ricleedo

MCP Server Boilerplate

by ricleedo
OverviewSchemaRelated ServersScoreDiscussions
JavaScript

Server Quality Checklist

42%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: get-mcp-docs is for server creation/development, while hello-world is for user interaction. There is no overlap in functionality or potential for confusion between these tools.

    Naming Consistency2/5

    The naming is inconsistent: get-mcp-docs uses kebab-case with a verb-object structure, while hello-world uses kebab-case but is a noun-phrase without a clear action verb. There is no predictable pattern across the tool set.

    Tool Count2/5

    With only 2 tools, this server feels too minimal for a 'boilerplate' purpose. A boilerplate typically provides foundational operations, but this set lacks basic CRUD or utility functions, making it insufficient for meaningful agent workflows.

    Completeness2/5

    For a boilerplate server, there are significant gaps: no create, update, delete, or configuration tools. The tools cover only documentation retrieval and a greeting, missing essential operations needed for building or managing an MCP server.

  • Average 2.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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

  • 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

  • Behavior2/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. 'Make an MCP server' suggests a creation/write operation, but doesn't clarify what exactly gets created (documentation? server instance?), whether this requires specific permissions, what the output format is, or any rate limits. The description provides minimal behavioral context beyond the implied creation action.

    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 extremely concise ('Make an MCP server') but this brevity comes at the cost of clarity and completeness. While it's not verbose, it's under-specified rather than efficiently informative. The single sentence doesn't earn its place by providing meaningful guidance beyond the tool name.

    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 annotations, no output schema, and a vague purpose, the description is insufficiently complete. The agent needs to understand what 'making an MCP server' entails, what the expected outcome is, and how this differs from the sibling 'hello-world' tool. The current description leaves too many open questions about the tool's function and appropriate usage 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 schema already documents the single 'name' parameter thoroughly. The description adds no additional parameter information beyond what's in the schema. According to the scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description.

    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?

    The description 'Make an MCP server' is a tautology that essentially restates the tool name 'get-mcp-docs' without clarifying what 'get' means or what 'docs' refers to. It doesn't specify whether this creates documentation, retrieves documentation, or builds a server instance. The description fails to distinguish this tool from its sibling 'hello-world' or provide a clear verb+resource combination.

    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's no mention of prerequisites, appropriate contexts, or comparisons to the sibling 'hello-world' tool. The agent receives zero direction about when this tool is applicable versus other approaches.

    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 carries the full burden of behavioral disclosure. 'Say hello to the user' suggests a read-only or informational action, but it doesn't specify if this involves side effects (e.g., logging, notifications), authentication needs, rate limits, or what the output looks like. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

    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 four words, with no wasted language. It's front-loaded with the core action ('Say hello'), making it easy to scan and understand quickly. Every word earns its place by directly contributing to the tool's purpose.

    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 (one parameter, no annotations, no output schema), the description is incomplete. It doesn't explain what 'say hello' results in (e.g., a message, a log entry), any behavioral traits, or usage context. While the tool is straightforward, the description lacks details needed for full agent understanding without relying on inference.

    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 parameter-specific information beyond what the input schema provides. With schema description coverage at 100%, the schema already documents the 'name' parameter as 'The name of the user'. Since the description doesn't elaborate on parameter usage or constraints, it meets the baseline of 3 for adequate but minimal value addition.

    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 'Say hello to the user' states a clear action (say hello) and target (the user), making the purpose understandable. However, it's somewhat vague about what 'say hello' entails (e.g., is it a greeting message, a notification, or something else?), and it doesn't explicitly differentiate from the sibling tool 'get-mcp-docs', though the distinction is implied by context.

    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 explicit guidance on when to use this tool versus alternatives. It implies usage for greeting users, but there's no mention of when-not-to-use scenarios, prerequisites, or comparisons to the sibling tool 'get-mcp-docs'. Without such context, the agent must infer usage based on the tool name and description alone.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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