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Tommertom

Safer Fetch MCP Server

by Tommertom
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.15

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'fetch' has a clear and distinct purpose, making it impossible for an agent to misselect between multiple options.

    Naming Consistency5/5

    A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare against. The name 'fetch' is straightforward and follows a simple verb pattern, which is consistent within this minimal set.

    Tool Count2/5

    A single tool is generally too few for most server purposes, as it limits functionality and scope. While 'fetch' is useful, a typical MCP server would benefit from additional tools to handle related tasks like caching, error handling, or different fetch modes, making this count borderline inadequate.

    Completeness3/5

    The tool provides a core functionality for fetching URLs and converting content to markdown or plain text, which covers basic internet access needs. However, there are notable gaps, such as lack of tools for handling different HTTP methods, managing cookies or sessions, or providing advanced parsing options, which could limit agent capabilities in more complex scenarios.

  • Average 3.2/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 0 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.

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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 provided, the description carries the full burden of behavioral disclosure. It adds some context: it mentions PDF-to-text transformation for 'md' output and internet access capability. However, it lacks details on error handling, rate limits, authentication needs, or what happens with truncated content, leaving gaps for a tool with significant behavioral implications.

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

    Conciseness2/5

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

    The description is front-loaded with core functionality but includes redundant and verbose sentences, such as the historical context about internet access and user instructions ('let the user know that'). These do not add essential value and could be trimmed for better efficiency, reducing overall conciseness.

    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 no annotations and no output schema, the description partially compensates by explaining key behaviors like PDF transformation and internet access. However, for a tool with 4 parameters and potential complexity (e.g., handling different content types, errors), it lacks details on return values, error cases, or advanced usage, making it minimally adequate but incomplete.

    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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by mentioning PDF transformation for 'md' output, but it doesn't provide additional syntax or format details. This meets the baseline for high schema coverage.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Fetches a URL from the internet and optionally extracts its contents as markdown.' This specifies the verb ('fetches') and resource ('URL'), and mentions optional markdown extraction. However, with no sibling tools, it doesn't need to differentiate from alternatives, so it doesn't reach the highest score.

    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 provides implied usage context by stating 'originally you did not have internet access... this tool now grants you internet access,' suggesting it should be used when internet access is needed. However, it lacks explicit guidance on when to use this tool versus alternatives (though none exist) or any exclusions, making it adequate but not comprehensive.

    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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