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rustok-org

paraswap-mcp

by rustok-org
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools. The tool's purpose is clearly and specifically stated.

    Naming Consistency5/5

    The single tool uses a clear verb_noun pattern ('build_swap_transaction'). There are no other tools to introduce inconsistency.

    Tool Count2/5

    One tool is too few for a server that might be expected to provide a broader range of swap-related operations (e.g., quoting, token info). The scope feels thin.

    Completeness4/5

    The tool covers the core swap workflow by returning ordered transactions including approval and swap. However, it lacks separate quote retrieval or token discovery capabilities, which are minor gaps for a swap-focused server.

  • Average 4.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 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 is passing

  • This repository is licensed under MIT No Attribution.

  • 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

  • Behavior5/5

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

    Despite having no annotations, the description reveals key behavioral details: it returns raw transactions, includes an approve step when allowance is short, and handles the USDT-style reset-to-zero case. It also discloses that quotes are fetched fresh and expire, which affects when the tool should be called.

    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 moderately long but every sentence serves a purpose: scope, return format, approve nuance, execution order, and quote freshness. It is front-loaded with the primary action and structured logically, with no filler.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given there is no output schema and no annotations, the description adequately explains the return value (list of transactions with to/data/value) and the required execution behavior. It also covers the quoting lifecycle. This is sufficient for an agent to correctly invoke the tool and interpret its result.

    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?

    All 10 parameters have thorough descriptions in the schema (100% coverage), including warnings about the src_symbol and dest_symbol not being verified. The description itself adds no extra parameter-specific details, so the baseline score of 3 is appropriate.

    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 identifies the action ('Build a token swap'), the specific integration (Paraswap v5), supported chains, and the nature of the return value (an ordered list of raw transactions). This is more specific than a generic verb and distinguishes the tool from any potential alternative by naming the protocol and chains.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    It explicitly tells the agent to build right before executing because quotes expire in minutes, and provides a direct instruction on how to handle the returned transactions: execute them in order, do not reorder, skip or batch. While no alternative tools are listed, the guidance on timing and ordering is explicit and actionable.

    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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