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gabrielmahia

wapimaji-mcp

by gabrielmahia
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Python
Remote

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: retrieving counties by drought phase, getting detailed status for a specific county, and sending an SMS alert. There is no overlap or ambiguity.

    Naming Consistency4/5

    Tool names mostly follow a verb_noun pattern, but 'sms_drought_alert' uses 'sms' as a verb while 'get_drought_alerts' and 'get_drought_status' use 'get'. This minor inconsistency prevents a perfect score.

    Tool Count5/5

    With only 3 tools, the server is tightly scoped to its purpose of drought alerting for Kenya. Each tool earns its place and the count is appropriate for the domain.

    Completeness4/5

    The tool set covers core needs: querying alerts, detailed status, and sending alerts. Minor gaps like listing all counties or historical data exist but are not critical for the primary use case.

  • Average 4/5 across 3 of 3 tools scored. Lowest: 3.4/5.

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

    • No community issues in the last 6 months
    • 33 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • 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.

  • This repository includes a glama.json configuration file.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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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

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided. Description only states the function (read counties) and explains the phase parameter. Does not disclose read-only nature, rate limits, data freshness, or any constraints beyond basic purpose.

    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?

    Two sentences: first states purpose, second explains the sole parameter. No redundancy, front-loaded with key action, and efficient use of space.

    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?

    No output schema, so description should explain what is returned (e.g., array of county names or objects). Missing details on empty results, errors, or pagination. For a simple tool, this is a significant gap.

    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?

    Schema has 0% description coverage, so description compensates by defining the integer parameter values: '1=Minimal, 2=Stressed, 3=Crisis, 4=Emergency, 5=Famine'. This adds necessary context beyond the schema's 'Min Phase' title and type.

    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?

    Clearly states 'Get all Kenya counties at or above a given drought phase', specifying exact verb and resource. Distinguishes from siblings: 'get_drought_status' likely for single county, 'sms_drought_alert' for sending alerts. No confusion with other tools.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does 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 like 'get_drought_status' or 'sms_drought_alert'. Does not mention prerequisites or context for invocation. Agent must infer based on name alone.

    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?

    Highlights destructive side effect ('sends real SMS in production') and sandbox option, but does not cover other behaviors like rate limits, costs, or failure modes.

    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?

    Very concise: three sentences with purpose, warning, and parameter meanings. No wasted words, information is front-loaded.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple SMS sending tool, the description covers purpose, parameters, and destructive behavior. Missing return value description, but given no output schema, it's adequate.

    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?

    Adds valuable details beyond the schema: phone_numbers format (E.164), message max length (160 chars), and sender_id requirement. Schema only provides basic types.

    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?

    Clearly states 'Send a drought alert SMS via Africa's Talking.' Uses specific verb (send) and resource (SMS), and distinguishes from sibling tools (get_drought_alerts, get_drought_status) which are read-only.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly warns about destructive nature and provides sandbox testing guidance. However, lacks explicit alternatives or when-not-to-use conditions.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description discloses return values (drought phase scale, rainfall deficit, population affected). It does not mention authorization or side effects, but for a read-only get operation, this is adequate.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is two sentences plus a parameter line, front-loading purpose and return format. Every sentence adds value with zero waste.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given no output schema, the description explicitly lists return fields (phase, deficit, population). It also distinguishes from siblings. Missing details like error handling or rate limits, but these are not critical for this simple tool.

    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 schema has 0% coverage (no description for 'county'). The description adds meaningful context: 'county: Kenya county name e.g. Turkana, Marsabit, Garissa', clarifying the parameter's domain and providing examples.

    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 tool gets current NDMA drought phase classification for a Kenya county, specifying the resource and scope. It distinguishes from siblings 'get_drought_alerts' and 'sms_drought_alert' by focusing on status vs alerts.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies use for current status queries, and examples of counties guide parameter input. While it doesn't explicitly state when not to use or mention alternatives, the purpose is clear enough for an agent to select appropriately.

    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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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.

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