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lianekai

mcp-dm8-server

by lianekai
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Server Quality Checklist

67%
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  • Latest release: v1.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: listing tables, describing a table's schema, and executing read-only queries. No overlap in functionality.

    Naming Consistency5/5

    All tools follow a consistent 'dm8_verb_noun' pattern (e.g., list_tables, describe_table, execute_query). Naming is predictable and uniform.

    Tool Count4/5

    3 tools is minimal but appropriate for a read-only database inspector. Covers basic operations without being wasteful.

    Completeness4/5

    The set covers listing tables, describing a table, and querying data. Lacks operations like retrieving row counts or schema listing, but is adequate for a focused read-only utility.

  • Average 3.7/5 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

  • This repository is licensed under ISC 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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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 provided; the description lacks disclosure of behavioral traits such as being read-only, authentication needs, or potential side effects. While it implicitly suggests a read operation, this is not explicitly stated, leaving room for ambiguity.

    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 a single, efficient sentence that conveys all necessary information without extraneous content. It is well-structured and avoids redundancy.

    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 simplicity and lack of output schema, the description adequately covers what is returned (column names, types, lengths, nullable). However, it might omit additional metadata like default values or precision, leaving minor gaps.

    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?

    Schema description coverage is 100%, with each parameter having a clear description. However, the tool description adds no further detail beyond the schema, maintaining a baseline score. No additional semantic value provided.

    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?

    Description explicitly states it returns column name, type, length, and nullable information, which clearly defines the tool's function. It distinguishes from siblings: dm8_list_tables lists table names, dm8_execute_query executes queries, while this tool provides table schema metadata.

    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 on when to use this tool vs alternatives. The description implies it is for obtaining table structure, but it does not mention situations where dm8_list_tables or dm8_execute_query would be more appropriate, nor any prerequisites or context.

    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?

    With no annotations provided, the description carries full burden but only states the basic operation. It does not disclose default behavior when schema is omitted, error handling, ordering, or permissions. For a listing operation, this leaves agents uncertain about side effects or constraints.

    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 a single, front-loaded sentence with no wasted words. It efficiently conveys the core functionality.

    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?

    For a simple list tool with one optional parameter, the description is mostly adequate. However, it lacks details on output format and what happens if schema is not specified (e.g., uses default schema). An explicit mention of the expected output (e.g., 'list of table names') would improve completeness.

    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 input schema is fully covered (100%), and the parameter description clarifies the default value. The tool description adds no additional meaning beyond the schema. Baseline 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 states that the tool returns all table names under a specified Schema, using a specific verb ('返回') and resource ('所有表名'). It distinctly differentiates from siblings: dm8_describe_table describes a specific table and dm8_execute_query runs arbitrary queries.

    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 the siblings. There is no mention of when not to use it, prerequisites, or alternatives. The description merely states the function without context.

    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 carries the full burden. It discloses the core behavioral trait (read-only, allowed statement types) but lacks details on error handling for non-allowed statements, authentication requirements, rate limits, or return format. This is adequate but not comprehensive.

    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 a single concise sentence that front-loads the key restriction. Every word serves a purpose, with no wasted information.

    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?

    For a simple read-only query execution tool with no output schema, the description provides enough information to understand its purpose and restrictions. However, it could be slightly improved by noting what happens if an invalid statement is submitted, but given the simplicity, it is largely complete.

    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 coverage is 100% with both parameters described. The description adds meaningful value by specifying the allowed statement types for the query parameter, going beyond the schema's '只读 SQL 语句'. This helps the agent construct valid queries.

    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 read-only SQL queries and lists exactly which statement types are allowed (SELECT/SHOW/DESCRIBE/EXPLAIN). This distinguishes it from sibling tools dm8_describe_table and dm8_list_tables, which are more specific table operations.

    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 provides clear context that only certain statement types are allowed, implicitly indicating when to use this tool (for custom read-only queries) and when not to (for modifications). However, it does not explicitly mention alternatives or exclusion cases beyond the allowed types.

    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.
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