Weather Israel MCP Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool performs a distinct step in the weather forecast workflow: opening the site, entering a city, selecting from a dropdown, and extracting the content. No two tools have overlapping purposes.
Naming Consistency3/5Most tools follow a 'verb_weather_forecast_city_israel' pattern, but 'get_weather_page_content' deviates by omitting 'israel' and using 'page_content' instead of 'forecast', causing inconsistency.
Tool Count4/5Four tools is a reasonable number for a focused weather query server, covering the essential steps without unnecessary complexity.
Completeness3/5The tools cover the basic flow of opening the page, searching, selecting, and retrieving content, but lack support for error recovery, multiple cities, or closing the browser, leaving minor gaps.
Average 3.4/5 across 4 of 4 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
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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 provided, so description must disclose all behavioral traits. It simply states 'clicks/selects' and returns success/failure, but lacks details on side effects (e.g., page changes, error states if dropdown empty). Minimal transparency for a UI interaction.
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?
Description is concise with two sentences covering action and return. No unnecessary words. Could benefit from a more structured format, but efficiency is good.
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?
With an output schema existing, the description need not explain return values. However, it omits error conditions, prerequisites (e.g., dropdown must be visible), and how it interacts with sibling tools. Adequate but not comprehensive for a UI automation tool.
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?
Input schema has no properties, so schema coverage is 100%. Baseline 3 applies. The description adds no parameter info because none exist; it correctly describes the tool's action without needing param details.
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 identifies the action (clicks/selects) and the target (first item in dropdown list of cities). It distinguishes from siblings like 'enter_weather_forecast_city_israel' which likely types input. However, it could be more explicit about the tool's role in the workflow.
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 on when to use this tool versus alternatives. It does not mention prerequisites or when selection is appropriate, leaving the agent to infer usage context.
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, and the description only mentions 'enters a city name' and a generic success/failure return message. It fails to disclose whether previous input is cleared, if the action triggers a search, or any side effects on the page state.
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 short and includes structured Args/Returns sections, making it easy to parse. However, it could be slightly more concise by removing redundant phrasing.
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?
For a simple action with one parameter, the description covers the basic purpose and return value. The presence of an output schema (though not detailed) reduces the need to explain return structure. However, it lacks mention of any prerequisites or page state.
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 0%, and the description adds a brief explanation for the 'city' parameter ('The name of the city to search for'), but this is essentially a restatement of the schema field title. No additional constraints, formats, or examples are provided.
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 action ('enters a city name') and the target ('search input field on the weather forecast page'), distinguishing it from siblings like 'select_weather_forecast_city_israel' which likely involves selection rather than text entry.
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 siblings such as 'select_weather_forecast_city_israel' or 'open_weather_forecast_israel', leaving the agent to infer context.
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?
Discloses that it opens a Chromium browser and navigates to a website, indicating it is a browser automation step. Returns success/failure message. Lacks details on side effects (e.g., new window, blocking behavior) or what happens on failure. Minimal but adequate.
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?
Extremely concise: two sentences covering action and return value. No extraneous information, front-loaded with the key action.
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?
For a simple tool with no parameters, the description is complete enough for its role. It explains what it does and what it returns. However, it could specify the exact URL or that the output is a simple status message, not page content.
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?
No parameters exist (0 params), so baseline score is 4. Description does not need to add parameter meaning beyond schema.
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 (opens a Chromium browser) and the target (Israeli weather forecast website). It distinguishes from sibling tools which handle city-specific actions and content retrieval. However, it could be more specific about exact URL or website 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?
No guidance on when to use this tool versus alternatives. Does not mention prerequisites, context, or when to use sibling tools like 'enter_weather_forecast_city_israel' or 'get_weather_page_content'.
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 provided, so description must carry full burden. It fails to disclose prerequisites (e.g., page must be loaded), error conditions, or return format details beyond 'text content' or 'error message'.
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?
Two short, front-loaded sentences with no filler. Every word adds value.
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?
For a simple tool with no parameters and an output schema, the description is largely adequate. However, it omits details about the output format and error semantics, which would improve completeness.
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?
With zero parameters, schema coverage is trivially 100%. The description adds no parameter information, but none is needed. Baseline of 4 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 verb 'extracts' and the resource 'weather forecast data from the currently loaded page', effectively distinguishing it from sibling tools which focus on navigation and city selection.
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?
No explicit guidance on when to use this tool versus siblings. While the context implies it should be used after navigation tools like open_weather_forecast_israel, the description does not state prerequisites or exclusions.
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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