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dinghuazhou

TOS MCP Server

by dinghuazhou
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Python
Remote

Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no ambiguity. get_object retrieves specific object content, list_buckets enumerates available buckets, and list_objects lists objects within a bucket. The three tools cover different operations without overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case formatting. get_object, list_buckets, and list_objects maintain perfect naming consistency throughout the toolset.

    Tool Count3/5

    With only 3 tools, this feels thin for a storage service interface. While the tools cover basic read operations, the absence of create, update, or delete operations makes this feel incomplete rather than minimal. The count is borderline for the apparent scope.

    Completeness2/5

    Significant gaps exist in this TOS storage interface. While it provides read operations (get_object, list_buckets, list_objects), it lacks essential CRUD operations like create_bucket, put_object, delete_object, or delete_bucket. Agents will encounter dead ends when trying to perform basic storage workflows.

  • Average 3/5 across 3 of 3 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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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 'Returns: A list of buckets' which adds some behavioral context about the output. However, it lacks details on permissions, rate limits, pagination, or error handling, which are important for a list operation with no annotations.

    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 very concise with two sentences that directly state the action and return value. It's front-loaded and has zero waste, making it efficient. However, it could be slightly improved by integrating the return statement more seamlessly.

    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 the tool has 0 parameters, no annotations, and no output schema, the description is minimal but covers the basic purpose and return. It's adequate for a simple list tool but lacks depth in behavioral context and usage guidelines, making it just sufficient for minimal viability.

    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 tool has 0 parameters, and the schema description coverage is 100%. With no parameters, the description doesn't need to add parameter semantics. The baseline for 0 parameters is 4, as it appropriately handles the lack of inputs without redundancy.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose3/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description states the tool 'List all buckets in TOS' which clearly indicates the verb (list) and resource (buckets). However, it doesn't differentiate from sibling tools like 'list_objects' which suggests it's vague about scope distinction. The purpose is understandable but lacks sibling 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?

    There is no guidance on when to use this tool versus alternatives like 'list_objects'. The description only states what it does without context or exclusions. This leaves the agent with no explicit or implied usage instructions.

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

  • 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 of behavioral disclosure. It mentions that it returns 'A list of objects' but lacks details on pagination behavior (implied by 'continuation_token'), rate limits, authentication requirements, or error handling. The description is minimal and doesn't adequately cover behavioral traits for a tool with multiple parameters.

    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 structured with clear sections for 'Args' and 'Returns', making it easy to scan. It's concise with no wasted words, though the parameter explanations are very brief. The front-loaded purpose statement is effective.

    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 the complexity of a tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on return format (e.g., structure of the object list), pagination behavior (critical given 'continuation_token'), error cases, and usage context. The minimal parameter explanations don't compensate for the missing behavioral and output information.

    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 lists all four parameters with brief explanations, but schema description coverage is 0%, so the schema provides no additional context. The parameter explanations are basic (e.g., 'The prefix to filter objects') and don't add significant semantic detail beyond what the parameter names imply. This meets the baseline for minimal compensation given the low schema 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 clearly states the action ('List all objects') and resource ('in a bucket'), making the purpose immediately understandable. It distinguishes from sibling tools like 'get_object' (which retrieves a specific object) and 'list_buckets' (which lists buckets rather than objects). However, it doesn't explicitly mention how it differs from siblings beyond the resource scope.

    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. The description doesn't mention sibling tools like 'get_object' for retrieving specific objects or 'list_buckets' for listing buckets, nor does it explain prerequisites or appropriate contexts for use.

    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?

    With no annotations provided, the description carries the full burden. It discloses the return behavior for text vs. binary formats, which is valuable context beyond basic retrieval. However, it lacks details on error conditions, permissions required, rate limits, or whether it's read-only (implied but not stated).

    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 appropriately sized and front-loaded with the core purpose. The Args and Returns sections are structured clearly, though the formatting with quotes might be slightly verbose. Every sentence adds value without redundancy.

    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 the tool's complexity (simple retrieval with 2 parameters) and no annotations or output schema, the description is moderately complete. It covers the purpose, parameters, and return behavior, but lacks context on usage guidelines, error handling, or integration with sibling tools, 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?

    The description adds significant meaning beyond the input schema, which has 0% coverage. It explains that 'bucket' is the bucket name and 'key' is the full key name for the object, clarifying what these parameters represent. For a tool with 2 parameters and low schema coverage, this compensates well.

    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 verb 'retrieves' and the resource 'an object from VolcEngine TOS', making the purpose explicit. However, it doesn't differentiate from sibling tools like list_objects, which might also retrieve object information in a different way.

    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 like list_objects. It mentions specifying the full key name but doesn't explain when this is preferable over listing objects or other operations.

    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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