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cajuflow

Hotmart MCP Server

by cajuflow
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct domain (products vs sales history) with no overlap in purpose, making it easy for an agent to select the correct tool.

    Naming Consistency5/5

    Both tools follow a consistent 'get_hotmart_<resource>' pattern, using snake_case and clear resource names.

    Tool Count2/5

    With only 2 tools, the server feels too minimal for a comprehensive Hotmart API integration; typical MCP servers offer more functionality.

    Completeness1/5

    The tool surface is severely incomplete, providing only read operations for products and sales, with no create, update, or delete capabilities.

  • Average 3.7/5 across 2 of 2 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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, the description must disclose behavioral traits. It implies a read-only operation and hints at pagination via 'max_results' and 'page_token' parameters, but does not explicitly state safe-to-call behavior, rate limits, or data volume considerations.

    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 front-loaded with a clear one-line purpose, followed by a parameter list. It is appropriately detailed for many parameters, but could be slightly more concise by removing redundant 'Options:' repetitions.

    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 complexity (13 parameters, no schema coverage, and an output schema exists), the description sufficiently covers parameter semantics. It does not detail the output format beyond 'JSON string,' but the output schema likely provides that information.

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

    Parameters5/5

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

    Schema description coverage is 0%, so the description carries the full burden. It provides detailed explanations for all 13 parameters, including enum options for transaction_status, payment_type, and commission_as, adding significant meaning beyond the schema's types and titles.

    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 'Get sales history from Hotmart account,' identifying the verb and resource. It does not explicitly differentiate from the sibling tool 'get_hotmart_products,' but the tool name itself provides differentiation.

    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?

    No guidance is provided on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or when not to use it.

    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 are provided, so the description alone must convey behavioral traits. It mentions the return format (JSON string) and lists parameters, but does not disclose authorization needs, rate limits, or potential impacts. For a read-only listing tool, this is minimally acceptable.

    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 starts with a clear one-line purpose, followed by a structured Args section. It is concise without unnecessary words, though the Args section could be slightly more compact. Still very readable and well-organized.

    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 5 optional parameters and the presence of an output schema (reducing need to describe return values), the description covers the main usage. However, it lacks any mention of authentication, rate limits, or pagination mechanics beyond the page_token parameter. It is complete enough for basic use but could be improved.

    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?

    The description adds significant meaning beyond the schema by enumerating each parameter with explanations, default values, and options (e.g., status and format enums, max_results limit, product_id format). With 0% schema coverage, this is crucial and well done.

    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 'Get list of products from Hotmart account', specifying the verb 'get' and the resource 'products'. This distinguishes it from the sibling tool 'get_hotmart_sales_history', which retrieves sales history.

    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 does not provide explicit guidance on when to use this tool vs the sibling tool, nor does it mention prerequisites or when not to use it. Implicitly, the difference is clear (products vs sales history), but no exclusions are stated.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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