Weather & WordPress MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tools are clearly split into two domains (weather and WordPress), but within each domain there is some overlap. For weather, get-alerts and get-forecast both provide weather information but for different purposes, which could cause confusion. For WordPress, get-latest-posts and get-posts-by-category both retrieve posts but with different filters, which might lead to misselection if the agent isn't clear on the distinction.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with hyphens (get-alerts, get-categories, get-forecast, get-latest-posts, get-posts-by-category). This makes them predictable and easy to understand, with no deviations in style or convention across the set.
Tool Count3/5
With 5 tools, the count is reasonable, but it feels thin for covering two distinct domains (weather and WordPress). Each domain only has 2-3 tools, which might not provide enough functionality for comprehensive workflows in either area, making it borderline appropriate.
Completeness2/5
There are significant gaps in both domains. For weather, there's no way to get current conditions or historical data, limiting coverage. For WordPress, there are no tools for creating, updating, or deleting posts or categories, making it read-only and incomplete for typical content management tasks.
Average 3.1/5 across 5 of 5 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
- CI status not available
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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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does ('Get weather forecast') but doesn't add any behavioral context beyond that—such as whether it's a read-only operation, potential rate limits, authentication needs, or what the forecast includes (e.g., temperature, precipitation). This is a significant gap for a tool with no 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 and front-loaded with a single, clear sentence that directly states the tool's purpose. There is no wasted language or unnecessary elaboration, making it efficient and easy to parse for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a weather forecasting tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the forecast includes (e.g., time range, weather elements), potential errors, or response format. This leaves significant gaps for an agent to understand how to use the tool effectively.
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 clear documentation for latitude and longitude parameters. The description adds no additional meaning beyond what the schema provides, as it doesn't explain parameter usage, format, or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.
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 clearly states the tool's purpose with a specific verb ('Get') and resource ('weather forecast for a location'), making it immediately understandable. However, it doesn't differentiate from sibling tools (e.g., get-alerts, get-latest-posts), which are unrelated to weather forecasting, so it doesn't need explicit sibling differentiation but could be more specific about the forecast type.
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. It doesn't mention any prerequisites, context for usage, or exclusions, leaving the agent to infer usage based on the name alone. This lack of explicit or implied guidelines reduces its helpfulness.
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 the full burden of behavioral disclosure. It states the action 'Get posts' but doesn't describe traits like read-only vs. destructive, authentication needs, rate limits, pagination, or error handling. For a tool with no annotations, this is a significant gap in transparency.
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 a single, efficient sentence that front-loads the core purpose without waste. It uses minimal words to convey the essential action and target, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given 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 incomplete for a retrieval tool. It lacks details on behavioral traits (e.g., safety, response format) and doesn't compensate for the absence of structured data. While concise, it fails to provide sufficient context for effective agent use.
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?
Schema description coverage is 100%, with the single parameter 'categorySlug' documented in the schema. The description adds no additional parameter semantics beyond what the schema provides (e.g., no examples beyond those in the schema, no constraints on valid categories). Baseline 3 is appropriate as the schema does the heavy lifting.
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 clearly states the verb 'Get' and resource 'posts from a specific category', specifying the target 'hafiz.blog (WordPress.com)'. It distinguishes from sibling tools like 'get-latest-posts' by focusing on category filtering, though it doesn't explicitly name alternatives. The purpose is specific but could be more differentiated.
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 like 'get-latest-posts' or 'get-categories'. It implies usage for category-based retrieval but lacks explicit when/when-not instructions or prerequisite context. This leaves the agent with minimal usage direction.
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 what the tool does but doesn't describe traits like whether it's read-only, requires authentication, has rate limits, returns structured data, or handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
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 a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple tool with one parameter. Every word earns its place.
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 covers the basic purpose but lacks behavioral context and usage guidelines. For a tool with no output schema, it doesn't describe return values, which would be helpful but isn't strictly required for a 3 score.
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?
Schema description coverage is 100%, with the single parameter 'state' fully documented in the schema (two-letter code format). The description adds no additional parameter semantics beyond implying the tool filters alerts by state. Baseline 3 is appropriate when the schema does the heavy lifting.
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 clearly states the verb ('Get') and resource ('weather alerts for a state'), making the purpose immediately understandable. It doesn't explicitly distinguish from siblings like 'get-forecast' or 'get-latest-posts', but the domain (weather alerts) is specific enough to imply differentiation. A 5 would require explicit sibling comparison.
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 like 'get-forecast' or other sibling tools. It doesn't mention prerequisites, exclusions, or contextual triggers for selecting this specific tool. The agent must infer usage from the purpose alone.
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 categories but doesn't disclose behavioral traits like whether it's a read-only operation, what format the categories are returned in, if there are rate limits, authentication requirements, or potential side effects. The description is minimal and lacks essential 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given 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 retrieval tool, it should ideally mention what the return format looks like (e.g., list of category objects with IDs and names) or any limitations. The current description provides only basic purpose without operational details needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. This meets the baseline expectation for tools without parameters.
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 clearly states the verb ('Get') and resource ('all categories available on hafiz.blog'), providing specific scope and platform context. It distinguishes from siblings by focusing on categories rather than alerts, forecasts, or posts. However, it doesn't explicitly differentiate from hypothetical category-related siblings.
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?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention when this tool is appropriate compared to sibling tools like 'get-posts-by-category' or indicate any prerequisites or constraints for usage.
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 the full burden. It states the tool retrieves posts but does not disclose behavioral traits such as rate limits, authentication needs, pagination, error handling, or what happens if no posts exist. This is a significant gap for a tool with no 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 a single, efficient sentence that front-loads the core functionality ('Get the 10 most recent posts') and includes essential context ('from hafiz.blog (WordPress.com)'). There is zero waste, and every word earns its place.
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 (0 parameters, no output schema, no annotations), the description is adequate for basic understanding but incomplete. It lacks details on return format, error cases, or behavioral constraints, which are important even for simple tools without structured data to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, and the baseline score is 4 for tools with no parameters, as it avoids unnecessary information.
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 specific action ('Get'), resource ('10 most recent posts'), and source ('hafiz.blog (WordPress.com)'). It precisely distinguishes this tool from sibling tools like get-categories or get-posts-by-category by specifying it fetches recent posts rather than categories or filtered posts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving recent posts from a specific blog, but it does not explicitly state when to use this tool versus alternatives like get-posts-by-category or provide any exclusions. The context is clear but lacks explicit guidance on tool selection.
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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