cn-holiday-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
query_holiday targets a single specific date while list_holidays returns full annual arrangements, so their purposes are clearly distinct. There is no practical overlap that would cause an agent to misselect.
Naming Consistency5/5Both tool names follow a consistent verb_noun pattern: query_holiday and list_holidays. The only minor difference is singular versus plural noun, which is natural and does not harm consistency.
Tool Count3/5Two tools is slightly thin, but each tool earns its place for the server's narrow read-only purpose. It falls at the borderline edge of the typical 3-15 tool range.
Completeness4/5The server covers the core holiday use cases: checking a specific day and listing a year's holiday schedule. Minor gaps exist, such as date-range lookups or upcoming-holiday queries, but they are workable conveniences rather than critical dead ends.
Average 3.8/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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 MIT 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.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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly discloses that the tool returns holiday periods, day counts, and adjusted work days, and that omitting the year returns all recorded years. This goes beyond a simple 'list holidays' to specify the output content, though it does not mention side effects or read-only nature (implicit).
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 a single sentence that is concise and front-loaded. It starts with the action and resource, provides the scoping condition, and enumerates the output contents. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one optional parameter and no output schema. The description covers the main functionality and parameter behavior. It does not specify the exact return format (e.g., array structure), but given minimal complexity and the presence of content details, it is sufficiently complete.
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?
Schema description coverage is 100% for the 'year' parameter, so the schema already explains it. The description paraphrases the parameter (year or all years) without adding significant new meaning. It is adequate but does not enhance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists statutory holiday arrangements for a given year or all recorded years, specifying included details (holiday periods, number of days, adjusted working days). This is a specific verb+resource that distinguishes it from a generic 'query' tool.
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 explicit guidance on when to use this tool vs the sibling tool 'query_holiday'. The description only implies its use for listing holidays, but does not mention alternatives or exclusions. It gives a default behavior hint (returns all years if year omitted), but no when-to-use or when-not-to-use comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the output categories and return fields but does not mention error handling, edge cases (e.g., invalid dates), or any side effects. For a read-only query, this is adequate 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose and key return data. There is zero fluff, and every clause contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, no output schema, no annotations), the description adequately covers what it does and what it returns. It could add notes on behavior for non-holiday days or invalid inputs, but overall it is sufficiently complete for an agent to use.
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?
Schema description coverage is 100% — the date parameter has its own format and example. The description repeats the format (YYYY-MM-DD) but adds no extra semantic value beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: querying whether a specific date is a legal holiday, compensatory workday, or ordinary day. It also specifies the return data (holiday name, interval, compensatory days), which distinguishes it from the sibling list_holidays that likely lists all holidays.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a single date ("查询某一天") but does not explicitly mention when to use this over the sibling tool list_holidays, nor any exclusion criteria. The context is understandable but lacking explicit guidance.
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
Copy to your README.md:
Score Badge
Copy to your README.md: