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Sen0E

MiaoMcp

by Sen0E
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools, calculator.calculate and time.get_current, target entirely distinct domains: arithmetic and time information. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow the same 'domain.action' pattern with snake_case: calculator.calculate and time.get_current. This is consistent and predictable.

    Tool Count3/5

    With only 2 tools, the server feels minimal but appropriate for a small utility purpose. It is borderline thin but not unreasonably so.

    Completeness4/5

    For a simple calculator/time server, the basic operations are covered. Minor gaps exist (e.g., timezone conversion or date arithmetic), but the core use cases are addressed.

  • Average 4.8/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 2 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 passing

  • 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

  • Behavior4/5

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

    No annotations are provided, so the description carries the full burden. It discloses a key safety behavior: '仅计算，不执行代码' (only calculate, not execute code), which is critical for a tool that takes an expression string. However, it does not mention edge cases like division by zero or error handling, though the output schema likely covers return format. This is good but not exhaustive.

    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 three concise sentences, each serving a distinct purpose: statement of function, usage trigger, and an example plus safety note. It is front-loaded with the core action and contains no fluff.

    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 simplicity of the tool (one parameter, output schema present, unrelated sibling), the description is complete. It covers purpose, usage, parameter format with an example, and a critical behavioral limitation. There is no missing information that would prevent a correct invocation.

    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 0% description coverage, so the description must compensate fully. It does so by providing an example of the expression parameter: '(12.5 + 7.5) * 2', and listing supported operators. This gives the agent a clear format and scope for the parameter, going beyond the schema's bare type definition.

    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: '计算一个基础算术表达式' (calculate a basic arithmetic expression), with specific operations listed (加减乘除, 取模, 乘方). It also provides a concrete example. The sibling tool time.get_current is completely unrelated, so differentiation is clear.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly states when to use the tool: '当用户询问加减乘除、取模或乘方结果时调用' (call when the user asks for results of addition, subtraction, multiplication, division, modulo, or exponentiation). It also gives a when-not: '仅计算，不执行代码' (only calculate, do not execute code), clarifying it should not be used for code execution.

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

  • Behavior4/5

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

    With no annotations, the description carries the burden of behavioral disclosure. It explains the timezone format and default, implying a read-only operation. However, it doesn't explicitly state that the operation has no side effects or mention error handling for invalid timezones, leaving a slight gap. The nature of the tool (getting current time) makes this less critical.

    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 two sentences long, with no unnecessary words. It front-loads the core purpose, then adds usage guidelines and parameter details in a logical order. Every sentence earns its place.

    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 simplicity of the tool (one optional parameter), the description is complete. The output schema exists to describe the return value, so the description needn't elaborate. It covers when to use, how to use, and the default behavior thoroughly.

    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 schema provides just the parameter name and default. The description adds crucial semantics: it explains what IANA names are, gives an example, and clarifies the default as Beijing time. This fully compensates for the zero schema coverage.

    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 function with a specific verb ('获取') and resource ('指定时区的当前日期和时间'), distinguishing it from the sibling calculator tool. It also provides usage context, making the purpose unambiguous.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly tells when to use the tool ('当用户询问现在几点、今天日期或星期时调用'), and even specifies the parameter format and default behavior. This is clear guidance with no alternative tools mentioned, but that's fine because the sibling is unrelated.

    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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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.

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