Skip to main content
Glama
BoosClues

MCP Server Boilerplate

by BoosClues
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 or ambiguity between them, making it easy for an agent to select the correct tool based on the task.

    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 phrase rather than a clear action. There is no predictable pattern across the tools, making the set chaotic and hard to interpret systematically.

    Tool Count2/5

    With only 2 tools, this server feels thin for a 'boilerplate' purpose, which typically implies a foundational or example set. The count is too low to adequately cover even basic MCP server operations, suggesting an incomplete or minimal implementation.

    Completeness1/5

    The server is severely incomplete for a boilerplate domain: it lacks essential tools for MCP server development (e.g., configuration, testing, deployment) and only includes a trivial 'hello-world' tool. There are significant gaps that would prevent agents from performing meaningful tasks.

  • Average 2.4/5 across 2 of 2 tools scored. Lowest: 1.7/5.

    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

  • Behavior1/5

    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. The description 'Make an MCP server' doesn't reveal any behavioral traits - it doesn't specify whether this is a read or write operation, what permissions are needed, whether it's idempotent, what happens on success/failure, or any side effects. For a tool with zero annotation coverage, this is completely inadequate.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness2/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    While the description is technically concise with just three words, it's under-specified rather than efficiently informative. The single sentence doesn't earn its place by providing meaningful information - it's too brief to be helpful. Good conciseness balances brevity with completeness, which this description fails to achieve.

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

    Completeness1/5

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

    Given that this is a single-parameter tool with no annotations and no output schema, the description is completely inadequate. It doesn't explain what 'making an MCP server' entails, what the tool actually does, what it returns, or how to interpret results. For even a simple tool, this level of incompleteness makes it unusable without additional 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?

    The input schema has 100% description coverage with a single parameter 'name' clearly documented as 'The name of the MCP server'. The description doesn't add any additional meaning beyond what the schema provides. With complete schema coverage, the baseline score of 3 is appropriate since the schema does all the parameter documentation work.

    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' in different words. It doesn't specify what 'make' means in this context (create, generate, fetch, etc.) or what 'MCP server' refers to. While it includes a verb+resource, it's too vague to distinguish from the sibling 'hello-world' tool or understand the actual purpose.

    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 context, prerequisites, or comparison to the sibling 'hello-world' tool. It doesn't indicate what scenarios would require 'making an MCP server' or what the expected outcome should be.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. 'Say hello' implies a read-only, non-destructive action, but it doesn't specify output format, side effects, or any behavioral traits like error handling or performance characteristics. This is a significant gap for a tool with zero annotation coverage.

    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 sentence ('Say hello to the user') that directly states the tool's purpose. It's front-loaded with zero waste, making it easy for an agent to parse quickly.

    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 simplicity (one parameter, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavioral context, usage guidelines, or output expectations, which are important even for simple tools to ensure correct invocation.

    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 semantics beyond what the input schema provides. With 100% schema description coverage (the 'name' parameter is fully documented in the schema), the baseline score is 3. The description doesn't compensate with additional context about parameter usage or constraints.

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

    Purpose4/5

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

    The description 'Say hello to the user' clearly states the tool's action (say hello) and target (the user), providing a specific verb+resource. However, it doesn't explicitly differentiate from its sibling tool 'get-mcp-docs', which appears unrelated but could benefit from clearer distinction in a broader 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 guidance on when to use this tool versus alternatives. There's no mention of context, prerequisites, or exclusions, leaving the agent to infer usage based solely on the tool name and purpose.

    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

new-MCP-builder MCP server

Copy to your README.md:

Score Badge

new-MCP-builder 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/BoosClues/new-MCP-builder'

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