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YeomYuJun

Tibero MCP Server

by YeomYuJun
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: execute_sql handles arbitrary SQL queries, while get_table_info provides metadata about a specific table. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (execute_sql and get_table_info). The naming is predictable and readable throughout the set.

    Tool Count2/5

    With only 2 tools, the server feels thin for a database interaction domain. Core operations like listing tables, describing schemas, or managing connections are missing, making it under-scoped for typical database workflows.

    Completeness2/5

    The tool surface is severely incomplete for a Tibero database server. It lacks basic CRUD lifecycle coverage (e.g., no tools for listing databases/tables, creating/dropping tables, or managing transactions), which will cause significant agent failures in database tasks.

  • Average 2.9/5 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

  • Behavior2/5

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

    With no annotations provided, the description carries full burden for behavioral disclosure. It states the action but doesn't mention critical traits like whether this is read-only or destructive, what permissions are needed, error handling, or result formatting. For a database execution tool, this leaves significant gaps in understanding its behavior.

    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 with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information without unnecessary elaboration.

    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?

    For a database execution tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after execution (e.g., returns results, affects data), error conditions, or security implications, leaving the agent with incomplete context for safe and effective use.

    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 the single parameter 'query' fully documented in the schema. The description adds no additional meaning about parameter syntax, valid SQL types, or constraints beyond what the schema provides, meeting the baseline for high 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 ('Execute') and target ('SQL query on the Tibero server'), providing specific verb+resource information. However, it doesn't differentiate from the sibling tool 'get_table_info', which might also involve SQL queries or database operations, so it doesn't fully distinguish from alternatives.

    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 'get_table_info'. There's no mention of appropriate contexts, exclusions, or prerequisites for executing SQL queries, leaving the agent without usage direction.

    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 for behavioral disclosure. While 'Get detailed information' implies a read-only operation, it doesn't specify what 'detailed information' includes, whether there are permission requirements, rate limits, error conditions, or what format the information comes in. This leaves significant behavioral gaps.

    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 gets straight to the point with zero wasted words. It's appropriately sized for a simple tool with one parameter and is perfectly front-loaded.

    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?

    For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'detailed information' means in terms of return values, doesn't address potential errors or constraints, and doesn't help differentiate from the sibling SQL execution tool. The context demands more completeness than provided.

    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 schema description coverage is 100% with the single parameter 'table_name' well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline for high schema coverage without adding extra value.

    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 ('Get detailed information') and target resource ('about a table'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'execute_sql' which could also provide table information through SQL queries, so it doesn't reach the highest score.

    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 the sibling 'execute_sql' tool, nor does it mention any prerequisites, context, or exclusions. It simply states what the tool does without helping the agent choose between alternatives.

    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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