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leonardtan13

whatsapp-web-mcp

by leonardtan13
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TypeScript
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct concern: listing chats, reading messages from a specific chat, and checking connection status. No functional overlap exists.

    Naming Consistency4/5

    All tools use snake_case and verbs or nouns clearly. 'list_chats' and 'read_chat' follow verb_noun pattern; 'whatsapp_status' slightly deviates but is still clear and consistent in style.

    Tool Count4/5

    With 3 tools, the server covers core read operations and status checking. The count is minimal but appropriate for a focused read-only WhatsApp interface.

    Completeness2/5

    The server lacks any write operations (e.g., send message, create chat). For a comprehensive WhatsApp tool set, these are significant gaps that limit agent functionality.

  • Average 3.5/5 across 3 of 3 tools scored. Lowest: 2.9/5.

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

    • No community issues in the last 6 months
    • 1 commit 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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  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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. It adds 'recent' and 'untrusted user content' but omits behavioral details like whether it is read-only (implied), rate limits, pagination, or error handling. Minimal value beyond the basic read action.

    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, no waste. The first sentence states the core purpose, the second adds a security note. Perfectly concise for the minimal information provided.

    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?

    With no output schema, no annotations, and 0% parameter coverage in the schema, the description is insufficient for an agent to use the tool effectively. It does not describe return format, error cases, or parameter semantics, leaving significant gaps.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%. The description does not explain any of the three parameters (limit, chatId, fromMe). For a tool with 3 parameters and no schema descriptions, the description fails to add meaning—the agent has no idea what fromMe does or how limit behaves.

    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 verb 'read' and the resource 'recent messages from one WhatsApp chat by id'. It distinguishes from sibling tools: list_chats lists chats, whatsapp_status deals with status, so purpose is specific and unambiguous.

    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 does not provide guidance on when to use this tool vs alternatives. It lacks context such as prerequisites, exclusion criteria, or when not to use it. The only addition is a security note about untrusted content, which is not usage guidance.

    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?

    Without annotations, the description carries the full burden. It only discloses that message content is not returned. Other behaviors like ordering, pagination (implied by limit), and what happens with empty results are not mentioned. This is minimal disclosure.

    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 with no fluff. The first sentence front-loads the main purpose, and the second adds an important limitation. 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?

    For a tool with 2 simple parameters, no output schema, and no annotations, the description is moderately complete. It clarifies the scope and a key omission but lacks detail on result ordering, pagination behavior, and return structure, which could affect agent decision-making.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so the description should compensate, but it does not mention the 'limit' or 'includeArchived' parameters at all. The agent gains no additional meaning beyond the schema property names and constraints.

    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 verb 'list' and the resource 'recent WhatsApp chats visible to this server'. It also notes a key limitation (message content not returned), which differentiates it from sibling tools like 'read_chat' that likely return message content.

    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 explicit guidance is provided on when to use this tool versus alternatives or when not to use it. The description does not mention prerequisites, ordering, or context that would help an agent decide.

    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?

    No annotations are provided, so the description carries the full burden. It fully discloses the tool's function (checking connection state) and clarifies it does not read messages, ensuring transparency about 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 extremely concise with two sentences that are front-loaded and contain no extraneous information.

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

    Completeness5/5

    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), the description is fully complete. It explains what the tool does and what it doesn't do, covering all necessary context.

    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 tool has zero parameters and schema coverage is 100%, so the description does not need to add parameter details. The baseline of 4 is appropriate.

    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 checks the local WhatsApp Web connection state and explicitly distinguishes itself from siblings by noting it does not read messages.

    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 usage for checking connection status without reading messages, which indicates when to use and provides a clear context. It lacks explicit when-not-to-use but is sufficient for a simple status tool.

    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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