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yripper

Remote MCP Server on Cloudflare

by yripper
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TypeScript
Hybrid

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.

    Naming Consistency5/5

    A single tool inherently has consistent naming, as there are no other tools to compare it against. The name 'get_list_tweets' follows a clear verb_noun pattern.

    Tool Count2/5

    One tool is generally too few for a server's purpose, as it limits functionality and suggests an incomplete or narrow scope. This is borderline inadequate for typical MCP server operations.

    Completeness2/5

    Inferring the domain as Twitter list management, the tool surface is severely incomplete. It only allows getting tweets from a list, with no capabilities for creating, updating, deleting lists, or interacting with tweets beyond retrieval, leading to significant gaps.

  • Average 2.9/5 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

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  • 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

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden. It mentions 'Get tweets' but doesn't disclose behavioral traits like read-only vs. destructive, authentication needs, rate limits, or response format. This leaves the agent with insufficient information for safe invocation.

    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, clear sentence with zero waste, making it highly concise and well-structured. It efficiently conveys the core purpose without unnecessary elaboration.

    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?

    Given no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects, usage context, or return values, making it inadequate for a tool with parameters and potential complexity.

    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 both parameters (list_id and max_results). The description adds no additional meaning beyond what the schema provides, such as format details or usage tips, meeting the baseline for high 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 'Get tweets from a specific list' clearly states the action ('Get') and resource ('tweets from a specific list'), making the purpose understandable. However, it lacks specificity such as mentioning retrieval or listing, and with no sibling tools, it doesn't need to differentiate, so it's not a 5.

    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 provides no guidance on when to use this tool, such as prerequisites, alternatives, or context. It simply states what it does without indicating usage scenarios, which is a significant gap.

    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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