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reiple

clickhouse-mcp-server

by reiple
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a unique and clearly defined purpose. There is no overlap; an agent can easily distinguish between describing a table, listing databases, listing tables, and running arbitrary queries.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (describe, list, list, run). The naming is predictable and intuitive.

    Tool Count5/5

    With four tools, the server is well-scoped for its read-only metadata and querying purpose. Each tool is essential and provides a distinct function without unnecessary bloat.

    Completeness4/5

    The tool set covers the core operations for inspecting a ClickHouse server's schema and executing queries. While some advanced metadata operations (e.g., listing table engines) are missing, the generic run_select_query tool can compensate for many gaps, making the surface reasonably complete.

  • Average 4/5 across 4 of 4 tools scored. Lowest: 3.4/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 1 commit 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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  • This repository includes a README.md file.

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

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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, and the description only says it 'describes columns' without disclosing side effects, permissions, or cost. For a read-only metadata tool, this is minimal but not misleading.

    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 a single sentence, efficiently conveying the tool's output. However, it could be structured to front-load critical information like required parameters.

    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?

    With an output schema present, return values are covered. The description is sufficient for this simple tool, though it could benefit from noting that database is optional.

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

    Parameters2/5

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

    Schema coverage is 0%, and the description does not add meaning beyond parameter names (table and database). It lacks examples, format details, or constraints that could help an agent construct valid arguments.

    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 returns column metadata (name, type, default expression, comment) for a table, distinguishing it from sibling tools like list_databases and list_tables.

    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 implies use when column details are needed but provides no explicit guidance on when or when not to use, nor does it mention alternatives like run_select_query.

    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, the description carries full burden but only states 'list all databases,' offering no behavioral details such as auth requirements, performance, or scope. It lacks transparency beyond the basic operation.

    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 with no unnecessary words or repetition, efficiently conveying the tool's purpose.

    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?

    While the tool is simple with no parameters and an output schema exists, the description lacks additional context such as when to use it over sibling tools or any limitations, making it minimally complete.

    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?

    There are no parameters, and schema description coverage is 100% (trivially). The description adds no parameter information beyond the empty schema, meeting the baseline for high 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 verb 'List' and the resource 'databases available on the ClickHouse server,' making the purpose explicit and distinguishable from sibling tools like list_tables.

    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 versus alternatives, though the simple purpose and sibling names imply the context. No when-not or alternative suggestions are given.

    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, the description adds some behavioral info (returns table name, engine, row count) but omits details like permissions or side effects.

    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?

    Two sentences, front-loaded with purpose, no wasted words.

    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 an output schema exists and one parameter, the description covers the core functionality and return values adequately.

    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 explains the default database behavior for the optional parameter, adding meaning beyond the schema's 'default: null'.

    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 action 'List tables' and the resource 'database', and distinguishes it from siblings like list_databases and describe_table.

    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?

    Specifies the default behavior for the database parameter, but lacks explicit guidance on when to use or avoid this tool compared to siblings.

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

  • Behavior5/5

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

    With no annotations, the description fully discloses read-only enforcement (two layers), max_rows default and hard cap, and the 'truncated' field in the response. Nothing hidden.

    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?

    Front-loaded purpose, then details, no redundant text. Every sentence adds value. Efficiently conveys critical behavior.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Covers all essential aspects for a 2-parameter tool with output schema: what queries are allowed, safety measures, result limits, and response field. Complete for effective use.

    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?

    Adds significant meaning beyond the schema: clarifies query must be read-only, lists allowed commands, documents max_rows default and hard cap. Compensates for 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?

    Clearly states the tool runs read-only SQL queries against ClickHouse, specifying allowed statement types (SELECT/SHOW/DESCRIBE/EXISTS). Differentiates from sibling tools that handle specific metadata queries.

    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?

    Details result caps and data-modifying statement rejection, but does not explicitly compare to siblings for when to use this vs describe_table, etc. The purpose is clear enough for most agents.

    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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