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dontsovcmc

io.github.dontsovcmc/ozon-seller

by dontsovcmc
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.3.1

  • Disambiguation5/5

    Each tool has a distinct purpose: ozon_search discovers actions, ozon_execute executes general API calls, and ozon_execute_file handles file downloads. No overlap in core functionality.

    Naming Consistency5/5

    All tools follow the consistent pattern of 'ozon_' prefix with a verb_noun structure (search, execute, execute_file). No mixing of conventions.

    Tool Count4/5

    Only 3 tools, but they are designed as a meta-interface to a large API. The minimal set is appropriate for the gateway pattern, though it may feel thin for complex workflows.

    Completeness4/5

    The meta-approach covers the entire Ozon Seller API via search and execute, with a dedicated tool for file downloads. Minor gap: no direct tools for common operations, but the discovery mechanism mitigates this.

  • Average 3.9/5 across 3 of 3 tools scored. Lowest: 2.8/5.

    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 is passing

  • 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 to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior1/5

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

    The annotations indicate readOnlyHint=false, suggesting the tool may have side effects, yet the description only mentions downloading a file (a read operation). This creates a contradiction. The description does not disclose any behavioral traits such as auth requirements, rate limits, or side effects. Therefore, it is misleading and scores low.

    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 concise, with one sentence for purpose and a bullet-like list for arguments. It is front-loaded and easy to read. Every sentence contributes value.

    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?

    The description explains the tool's primary function and parameters, but lacks information on usage context, side effects, and differentiation from siblings. With a simple schema and output schema present, the description is adequate but not comprehensive.

    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?

    The description adds some meaning to parameters beyond the schema titles: it explains 'action' is an action ID, 'file_path' is a local path to save, and 'params_json' is a JSON object. However, it does not specify what actions are valid or the structure of params_json. Given that schema description coverage is 0%, the description partially compensates but remains vague.

    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 executes an Ozon Seller API action that results in downloading a file. The verb 'execute' and resource 'action' are specific. However, it does not differentiate from sibling tool 'ozon_execute' which likely also executes actions but without file download. This lack of distinction prevents perfect clarity.

    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. There is no mention of prerequisites, context, or conditions. The sibling tools are not referenced.

    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?

    Annotations indicate non-read-only; description confirms it executes an action, implying mutation, but lacks details on side effects or rate limits.

    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?

    Concise, front-loaded with purpose, and uses only four sentences including a structured Args list.

    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?

    Covers essential usage and parameters; output schema exists so no need for return details, though the description could clarify params_json is a string.

    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?

    With 0% schema coverage, description fully explains both parameters: action is an ID from ozon_search with example, params_json is a JSON object matching the schema.

    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 the tool executes an Ozon Seller API action by ID, and distinguishes it from siblings by advising to use ozon_search first.

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

    Usage Guidelines4/5

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

    Explicitly instructs to use ozon_search before executing, providing clear usage context, though it does not mention ozon_execute_file or when not to use.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    Annotations declare readOnlyHint true, and the description adds behavioral context (searches by intent, parameter constraints). It does not contradict annotations and provides additional detail like domain filter options.

    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 concise with a clear purpose statement followed by a structured Args section. Every sentence adds value, no redundant content.

    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?

    The description covers the tool's purpose and all parameters. An output schema exists, so return value explanation is not required. It might lack details on error handling or empty results, but is sufficient for the tool's complexity.

    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?

    The description adds significant meaning beyond the schema: query is natural language, domain is an optional filter with a list of valid values, limit sets max results with default. This compensates for the 0% schema description coverage.

    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 the tool's purpose: 'Find available Ozon Seller API actions by intent.' It specifies a verb (Find) and resource (available actions), and distinguishes itself from sibling tools that execute actions.

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

    Usage Guidelines4/5

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

    The description lists parameters with explanations (query as natural language, domain filter with allowed values, limit with default). While it does not explicitly state when to use or avoid this tool, the sibling names strongly imply this is for discovery versus execution.

    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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