MCP Server Boilerplate
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools have completely distinct purposes: one is for creating MCP servers (get-mcp-docs) and the other is for greeting users (hello-world). There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool.
Naming Consistency2/5The naming is inconsistent: get-mcp-docs uses a verb-object format with hyphens, while hello-world is a phrase without a clear verb. This mixed convention lacks a predictable pattern, which could confuse agents trying to infer tool functions from names.
Tool Count2/5With only 2 tools, this server feels under-scoped for a 'boilerplate' purpose, which typically implies a foundational set of utilities. Such a low count limits functionality and suggests the server might not cover basic operations expected in a boilerplate context.
Completeness2/5For a boilerplate server, there are significant gaps: it lacks core operations like setup, configuration, testing, or deployment tools. The two tools provided (documentation and greeting) do not form a complete surface for building or managing MCP servers, leaving agents unable to perform essential 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.jsonto 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?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. 'Make an MCP server' suggests a creation/write operation but doesn't specify what gets created (files, configuration, documentation), whether it requires specific permissions, what the output format is, or any side effects. The description doesn't address error conditions, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is technically concise (three words), it's under-specified rather than efficiently informative. The single phrase 'Make an MCP server' doesn't provide enough context to be genuinely helpful. A truly concise description would front-load essential information about the tool's purpose and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given 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 description that provides minimal context, this is severely incomplete. The agent cannot determine what the tool actually does, what it returns, when to use it, or how it behaves. The description fails to compensate for the lack of structured metadata, leaving critical gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage with a single parameter 'name' documented as 'The name of the MCP server'. The description doesn't add any additional semantic context about this parameter beyond what the schema already provides. Since schema coverage is high, the baseline score of 3 is appropriate - the description neither enhances nor detracts from parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does 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 action is actually performed (e.g., retrieve documentation, create server files, generate configuration) or what resource is being manipulated. The description fails to distinguish this tool from its sibling 'hello-world' or explain what 'making' an MCP server entails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does 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 comparison with the sibling 'hello-world' tool. The agent receives no information about whether this is for development setup, documentation retrieval, or configuration generation.
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 to the user' implies a read-only output operation, but doesn't specify whether this creates any side effects, requires authentication, has rate limits, or what the actual output format is. It's minimal behavioral information for a tool that presumably just returns a greeting.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just four words, front-loaded with the core action. There's zero wasted language or redundancy. For a simple greeting tool, this brevity is appropriate and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is minimally complete. It tells what the tool does at a high level but lacks details about the return value format or any behavioral constraints. Without annotations and with no output schema, the agent would need to infer the response structure from the tool name and description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, with the single parameter 'name' clearly documented as 'The name of the user'. The description doesn't add any additional parameter information beyond what the schema provides, but with only one well-documented parameter and no complex semantics needed, this is adequate. The baseline would be 3 for high schema coverage, but the simplicity of the single parameter justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does 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 (user), but it's vague about what this actually does - is it a greeting message, a notification, or something else? It doesn't distinguish from the sibling tool 'get-mcp-docs' which is completely different in function. The purpose is understandable but lacks specificity about the output format or mechanism.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention any context for usage, prerequisites, or exclusions. With only one sibling tool that serves a completely different purpose (document retrieval), there's no explicit comparison or guidance about choosing between them.
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 the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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