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Jorisslagter

maillog-mcp

by Jorisslagter
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TypeScript
Remote

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 have clearly distinct purposes: one creates a new outgoing message, the other reads history of previously sent messages. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow the same verb_noun pattern (send_email, list_emails), making the set predictable and easy to navigate. The consistency is perfect for a two-tool surface.

    Tool Count3/5

    With only two tools, the server feels thin for a general email service, though the pair covers the two most essential actions. The count is borderline but not unreasonable for a narrowly scoped transactional email logging use case.

    Completeness4/5

    The core lifecycle of sending and verifying delivery is covered: create an email and list sent emails with status. A minor gap is the lack of a single-email detail endpoint or pagination control, but agents can likely work around that using list_emails.

  • Average 3.9/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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

  • This repository is licensed under MIT 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

  • Behavior3/5

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

    There are no annotations, so the description carries the behavioral burden. It discloses ordering ('newest first') and result fields ('delivery status and open/click counts'), which is useful, but doesn't mention pagination defaults, filtering semantics, or that the operation is read-only beyond the word 'List.'

    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 convey the resource, ordering, result contents, and the intended use case without waste. The key purpose is front-loaded and the use case sentence 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?

    The tool is simple, but with no output schema and no annotations, the description should cover more ground. It names key return fields and the use case, yet omits pagination behavior, default limits, and possible status filter values, leaving gaps an agent must infer.

    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?

    Schema description coverage is only 33%, and the description does not compensate: it never explains limit, offset, or status filtering behavior. Status is documented in the schema, but limit and offset remain undocumented, and the description only hints at ordering rather than parameter usage.

    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?

    Description uses a specific verb ('List') with a clear resource ('emails previously sent through Maillog') and adds ordering and output fields. It clearly distinguishes from the sibling tool send_email by focusing on checking whether a message went out.

    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 says 'Use this to check whether a message actually went out,' which gives a concrete condition for selecting this tool. It doesn't spell out when-not-to-use or name the sibling explicitly, but the description frames this as the read-side counterpart to sending.

    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 of behavioral disclosure. It usefully reveals that 'from' must use a verified domain and sandbox keys are restricted to a single recipient. However, it does not describe side effects, response behavior, failures, or rate limits, leaving meaningful gaps for a sending operation.

    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 with no wasteful preamble or redundant restating of the name. The key constraint is stated immediately after the core action, making it easy to parse.

    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 sandless mutation tool with no output schema and no annotations, this is only partially complete. It covers the most important prerequisite domain verification and sandbox behavior, but it omits body-field requirements, optional parameter semantics, and any indication of what happens after the email is accepted.

    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 50%, so the description must partially compensate. It adds important semantic constraints for 'from' (verified domain) and indirectly for 'to' (sandbox limit), but it says nothing substantive about cc, bcc, reply_to, html, text, or subject beyond what the schema already documents.

    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: sending a transactional email via Maillog. It clearly distinguishes itself from the sibling list_emails by operation, so an agent can tell the tools apart without inspecting schemas.

    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?

    It states the intended context (transactional email via Maillog) and gives operational restrictions: verified domains, sandbox keys. It does not explicitly point to list_emails as the alternative for reading, but the operation split is obvious and the eligibility guidance is sufficient.

    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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  • Evaluate tool definition quality.

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