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maillog-dev

maillog-mcp

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by maillog-dev
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    send_email and list_emails are clearly distinct: one creates a new email, the other reads previously sent emails. There is no overlap or ambiguity between the two operations.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun snake_case pattern, matching the broader MCP convention. The style is predictable and uniform across the small set.

    Tool Count3/5

    Two tools is on the thin side for a server, but the pair covers the core send-and-verify workflow implied by the Maillog domain. It is functional yet minimal, so the count is borderline appropriate.

    Completeness4/5

    The server covers the essential email send and delivery-check lifecycle with no obvious dead ends. Minor gaps exist, such as no single-email detail lookup or domain management, but the core workflow is workable.

  • Average 3.8/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 2 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 MIT License.

  • 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

  • Behavior3/5

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

    With no annotations, the description carries the disclosure burden. It adds a meaningful behavioral constraint: 'from' must be on a domain verified in Maillog, and sandbox keys may only send to the address the key was issued for. However, it does not disclose failure behavior, delivery semantics, or other side effects beyond the act of sending.

    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 long: the first states the purpose, the second states the key constraint. There is no filler, and the most important information is front-loaded before the caveat.

    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 an 8-parameter write operation with no annotations and no output schema, the description is minimally adequate: it gives the core purpose and one critical precondition. It omits response/error behavior, the need to supply html or text, and any guidance about selecting this tool over list_emails, leaving clear gaps.

    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 coverage is only 50%; from, to, html, and text have schema descriptions, while cc, bcc, subject, and reply_to do not. The description adds important meaning to 'from' by requiring a verified domain and to 'to' through the sandbox restriction, but it does not compensate for the wholly undocumented remaining parameters.

    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 uses a specific verb and resource: 'Send a transactional email through Maillog.' The action 'Send' immediately distinguishes this tool from the read-oriented sibling list_emails, so an agent can tell them apart without inspecting the schema.

    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?

    There is no explicit when-to-use or when-not-to-use guidance. The phrase 'transactional email' implies the intended context, and the sibling list_emails is clearly a different operation, but no alternative or exclusion condition is named. Usage is only implied, not stated.

    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?

    With no annotations, the description carries the burden. It adds behavioral details by specifying ordering ('newest first') and return fields ('delivery status and open/click counts'). However, it doesn't address pagination defaults, rate limits, or the meaning of status values.

    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 short sentences with the action front-loaded. Every clause adds information—resource, ordering, output, and use case—leaving no filler.

    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?

    The description covers the essential return contents and use case, but with no output schema and no annotations, it leaves some gaps around default limit, response format, and failure behavior. Adequate for a simple list but not fully complete.

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

    Parameters2/5

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

    Only status has a schema description; limit and offset have none, and the description doesn't explain them. The schema coverage is 33%, below the 50% threshold, so the description needed to compensate and didn't.

    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 states a clear action ('List') and target resource ('emails previously sent through Maillog'), and it notes output contents ('delivery status and open/click counts'). This makes it easily distinguishable from its only sibling, send_email, which is a write operation.

    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 phrase 'Use this to check whether a message actually went out' provides an explicit use case. It doesn't spell out exclusions or name send_email, but the context of listing vs sending makes the choice clear.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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