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gawakawa

Pursuit MCP

by gawakawa
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Python
Remote

Server Quality Checklist

58%
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 has a single, clear purpose: searching the Pursuit database for PureScript-related content. An agent cannot misselect between non-existent alternatives.

    Naming Consistency5/5

    The single tool name 'search_pursuit' follows a consistent verb_noun pattern, using snake_case. There are no other tools to compare against, so no inconsistency can exist. The naming is clear and predictable for its isolated context.

    Tool Count2/5

    A single tool is too few for a server named 'Pursuit MCP', which suggests broader functionality related to PureScript's Pursuit ecosystem. While the tool covers search, obvious gaps exist (e.g., no tools for browsing packages, viewing documentation details, or managing favorites), making the server feel thin and incomplete for its implied domain.

    Completeness2/5

    The tool set is severely incomplete for a Pursuit-related server. It only provides search functionality, missing essential operations like retrieving detailed package information, listing categories or modules, or accessing documentation beyond search results. This creates significant gaps that will limit agent capabilities in handling PureScript queries effectively.

  • 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
    • 17 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 full burden. It mentions the return format (JSON string) and default limit, but lacks details on error handling, rate limits, authentication needs, or search behavior (e.g., partial matches, case sensitivity). For a search tool with zero annotation coverage, this is insufficient.

    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 well-structured with clear sections (Args, Returns) and front-loaded purpose. It's concise with no wasted words, though the 'Returns' section could be integrated more smoothly. Every sentence adds value.

    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?

    Given the tool's moderate complexity (2 parameters, search functionality), the description covers purpose, parameters, and return format. With an output schema present, it doesn't need to detail return values. However, it lacks behavioral context like error cases or search specifics, leaving some gaps.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so the description must compensate. It explains both parameters: 'query' as search query for function names, type signatures, or keywords, and 'limit' as maximum results with a default. This adds meaningful context beyond the bare schema, though it could detail query syntax or limit constraints more.

    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 searches for PureScript functions, types, and documentation, specifying the resource (Pursuit) and verb (search). It distinguishes what can be searched (functions, types, documentation) but doesn't need sibling differentiation since there are no sibling tools. The purpose is specific and unambiguous.

    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 versus alternatives, prerequisites, or exclusions. It only states what the tool does, not the context for its application. With no sibling tools, this is less critical, but still lacks usage context.

    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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