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Rajath2000

Email MCP Server

by Rajath2000
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: listing emails, reading full content, and summarizing. No overlap in functionality, making it easy for an agent to select the correct tool.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with snake_case naming (list_recent_emails, read_email, summarize_email), providing clear and predictable naming.

    Tool Count3/5

    With only 3 tools, the server is on the thin side but acceptable for a focused demo or specialized task. However, it may feel insufficient for broader email management.

    Completeness2/5

    The server lacks essential email operations like sending, deleting, or searching, limiting its usefulness. It only covers reading and summarizing, leaving significant gaps for typical email workflows.

  • Average 3.7/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 3 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

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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 burden. It adds that it is an 'AI summary' and a 'Demo', but does not disclose behavioral traits such as idempotency, rate limits, error handling, or whether it requires authentication beyond what is assumed.

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

    Conciseness4/5

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

    The description is a single sentence with no unnecessary words. The parenthetical 'Internal Server-Side Summarization Demo' is slightly extraneous but does not detract significantly. It is appropriately front-loaded.

    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?

    Given a single parameter and no output schema, the description explains the input and action. However, it does not mention how to obtain the email ID or what the output format is, which would be helpful given the sibling tools. Adequate but not complete.

    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 100% with a clear description for 'id'. The description adds 'by ID' but no further semantics. Baseline 3 is appropriate as the schema already documents the parameter adequately.

    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 'Get', the resource 'AI summary of a specific email', and the method 'by ID'. It distinguishes from siblings: list_recent_emails lists emails, read_email reads full content, while this provides a summary.

    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?

    The description implies usage for obtaining a summary rather than the full email or list, but does not explicitly state when to use or when not to use, nor does it mention prerequisites like fetching the email ID first.

    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?

    The description discloses that the tool returns only recent emails without bodies, implying a read-only, non-destructive operation. However, since no annotations are provided, it does not explicitly state its side-effect free nature, required authentication, or the exact sorting criteria. This is adequate but could be more explicit.

    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, concise sentence that front-loads the core purpose. Every word is meaningful, with no redundancy or filler.

    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?

    The description does not specify what fields are returned in the email list (e.g., subject, sender, timestamp), nor does it mention any pagination or handling of large result sets. Given the lack of an output schema, the description should provide more detail on the response format to be fully complete.

    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 already provides a description for the only parameter 'limit' (default 5). The tool description adds no additional semantic value beyond what the schema offers, so it meets the baseline of 3.

    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 action ('List'), the resource ('most recent emails'), and the scope ('inbox'), while also specifying what is excluded ('without bodies'). This distinguishes it from sibling tools 'read_email' (which likely includes bodies) and 'summarize_email' (which would provide a summary).

    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?

    The description implies that if bodies are needed, one should use 'read_email' instead, but it does not explicitly state when to use this tool versus its siblings. No direct guidance on prerequisites or alternatives is provided beyond the implication from the 'without bodies' qualifier.

    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?

    No annotations provided, so the description carries full burden. It states it is a read operation, which is non-destructive, but lacks details on permissions, rate limits, or error handling.

    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?

    Single sentence, to the point, no unnecessary words.

    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 read tool with one parameter and no output schema, the description is adequate, though it could mention authentication or return format.

    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 100%, so the description adds minimal value beyond the schema's parameter description. The phrase 'full body content' describes the operation, not the parameter.

    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', the resource 'email by ID', and specifies 'full body content', distinguishing it from sibling tools 'list_recent_emails' and 'summarize_email'.

    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 when the full body of a specific email is needed, but does not explicitly state when not to use it or mention alternatives.

    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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