Weather MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation1/5
The tools have no coherent domain overlap, making them highly ambiguous as a set. 'get-alerts' and 'get-forecast' relate to weather, while 'get-feishu-doc' is unrelated (document retrieval), causing clear confusion about the server's purpose and tool selection.
Naming Consistency2/5Naming is inconsistent with mixed conventions: 'get-alerts' and 'get-forecast' use kebab-case with a 'get-' prefix, while 'get-feishu-doc' uses kebab-case but includes a non-English term, breaking pattern. The verbs are consistent ('get'), but the overall style lacks uniformity.
Tool Count2/5With only 3 tools, the count is too low for a coherent weather server, as it lacks essential operations like historical data or radar. The inclusion of an unrelated document tool further dilutes the scope, making the set feel incomplete and mismatched.
Completeness1/5The tool set is severely incomplete for a weather domain, missing basic CRUD operations like update or delete, and lacking coverage for key weather aspects (e.g., current conditions, historical data). The unrelated document tool creates a gap in domain coherence, making the surface unusable for weather-related tasks.
Average 2.9/5 across 3 of 3 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
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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. It states what the tool does but doesn't mention critical aspects like whether it's read-only, requires authentication, has rate limits, or what the output format looks like. This leaves significant gaps for an agent to understand how to interact with it safely and effectively.
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, clear sentence that efficiently conveys the core functionality without any wasted words. It's appropriately sized for a simple tool and front-loaded with essential information, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns complex alert data. It doesn't explain what 'weather alerts' entail (e.g., types, severity, timestamps) or how results are structured, leaving the agent with insufficient context to use the tool effectively beyond basic invocation.
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 description coverage is 100%, with the parameter 'state' fully documented in the schema (including format and constraints). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for adequate but unenriched parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('weather alerts for a state'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get-forecast' (which might provide different weather data), so it misses full sibling distinction.
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?
The description provides no guidance on when to use this tool versus alternatives like 'get-forecast' or 'get-feishu-doc'. It lacks context about prerequisites, exclusions, or specific scenarios where this tool is appropriate, offering only basic functional information.
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 full burden. It states the tool retrieves document content as plain text, which implies a read-only operation, but doesn't disclose important behavioral traits like authentication requirements, rate limits, error conditions, or what happens with different document types mentioned in the schema. The description is minimal and lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single Chinese phrase that communicates the core purpose efficiently. There's no wasted language, though one could argue it's almost too minimal. It's front-loaded with the essential information in compact form.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format the plain text output takes, how different document types are handled, authentication requirements, or error scenarios. For a tool that interacts with external documents, more operational context would be helpful.
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%, so the schema already fully documents the single parameter (docId). The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description '获取飞书文档内容(纯文本)' clearly states the action ('获取' - get/retrieve) and resource ('飞书文档内容' - Feishu document content) with specificity about the format ('纯文本' - plain text). It distinguishes from potential siblings by focusing on document content retrieval rather than alerts or forecasts, though it doesn't explicitly differentiate from hypothetical document-related tools.
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 prerequisites, context for use, or exclusions. While the sibling tools (get-alerts, get-forecast) are clearly different, there's no explicit comparison or usage context provided.
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 full burden for behavioral disclosure. It states it 'gets' data, implying a read-only operation, but doesn't specify whether this requires authentication, has rate limits, returns real-time vs. forecast data, or what format/timeframe the forecast covers. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.
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, clear sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information. Every word earns its place by specifying the action, resource, and target without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what the forecast returns (e.g., temperature, conditions, timeframe), whether it's free/paid, or any error conditions. For a weather tool that likely has important behavioral aspects, this minimal description leaves too much unspecified for effective agent 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%, with both parameters (latitude and longitude) fully documented in the schema. The description adds no additional parameter information beyond implying location is needed. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't compensate with any extra semantic context about parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'weather forecast for a location', making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'get-alerts' or 'get-feishu-doc', but those appear to be unrelated weather tools, so differentiation isn't critical here. The description avoids tautology by specifying what kind of forecast (weather) rather than just restating the name.
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?
The description provides no guidance on when to use this tool versus alternatives. While sibling tools like 'get-alerts' might be for weather alerts, there's no explicit mention of when to choose forecast over alerts or other weather-related tools. The description simply states what it does without context about appropriate use cases or prerequisites.
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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