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christian561

Gel Database MCP Server

by christian561
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TypeScript
Hybrid

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves weather alerts for states, while the other retrieves forecasts for locations. There is no overlap in functionality, and an agent can easily differentiate between them based on their descriptions.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern (get-alerts and get-forecast). The hyphenated style is uniform across all tools, making them predictable and easy to understand.

    Tool Count2/5

    With only two tools, the server feels thin for a weather database domain. It lacks essential operations like updating data, searching historical records, or managing locations, which limits its utility for comprehensive weather-related tasks.

    Completeness2/5

    The tool surface is severely incomplete for a database server. It only provides read operations (get-alerts and get-forecast) with no create, update, delete, or search capabilities. This creates significant gaps that will hinder agents from performing full database workflows.

  • Average 2.9/5 across 2 of 2 tools scored.

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

    • 0 of 1 community issues answered or closed 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

  • This repository is licensed under ISC License.

  • This repository includes a README.md file.

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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 describe traits like rate limits, authentication needs, error handling, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core purpose 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 tool that likely returns complex alert data. It doesn't explain what the alerts include, how they're formatted, or any limitations, leaving the agent with insufficient context for effective 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?

    The description doesn't add any parameter-specific information beyond what's in the input schema, which has 100% coverage and fully documents the 'state' parameter. This meets the baseline score of 3, as the schema adequately handles parameter semantics without needing extra description.

    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 specific and understandable. However, it doesn't explicitly differentiate from its sibling tool 'get-forecast', which likely provides different weather data, so it doesn't reach the highest score.

    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 its sibling 'get-forecast' or any alternatives. It lacks context about usage scenarios, exclusions, or prerequisites, offering only a basic statement of function.

    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 the full burden of behavioral disclosure. It states what the tool does but doesn't describe any behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, or what the response format might be. This is inadequate for a tool with zero 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, clear sentence that efficiently conveys the core purpose without any unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

    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 that there are no annotations and no output schema, the description is incomplete. It doesn't provide enough context about behavioral aspects, response format, or how this tool differs from its sibling. For a tool with this level of complexity and lack of structured data, the description should do more to compensate.

    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 schema description coverage is 100%, with both parameters (latitude and longitude) well-documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema, so it meets the baseline score of 3.

    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 forecast for a location'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get-alerts', which likely provides different weather-related information, so it doesn't achieve the highest score.

    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 the sibling 'get-alerts' or explain the difference between getting a forecast versus alerts, leaving the agent without context for 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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