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mcp-clickhousex

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Python
Remote

MCP ClickHouse 工具

CI PyPI Python 3.13+ License: MIT

一个用于 ClickHouse 的只读 Model Context Protocol (MCP) 服务器，支持元数据发现、资源、参数化 SELECT 查询、SHOW 内省、查询分析，以及针对大型结果集的快照模式，并带有基于配置文件的配置和严格的禁止 DML/DDL 执行。

要求： Python 3.13+、正在运行的 ClickHouse 实例，以及通过环境变量或配置文件提供的连接信息。

快速开始

设置 DSN 并使用 MCP Inspector 运行服务器：

# Option 1: Run directly with uvx (no clone needed)
export MCP_CLICKHOUSE_DSN="http://default:@localhost:8123/default"
npx -y @modelcontextprotocol/inspector uvx mcp-clickhousex
# Option 2: Run from source (clone repo, then)
export MCP_CLICKHOUSE_DSN="http://default:@localhost:8123/default"
npx -y @modelcontextprotocol/inspector uv run main.py

Related MCP server: io.github.Aguantar/clickhouse-dataops-mcp

配置

所有设置均使用 MCP_CLICKHOUSE 前缀。扁平环境变量（例如 MCP_CLICKHOUSE_DSN）是在拥有单个连接时配置默认配置文件的直接方式。对于多个配置文件，建议使用用户级 config.json 文件。

单个连接： 通过环境变量进行配置。

# Connection DSN (required).
export MCP_CLICKHOUSE_DSN="http://user:password@host:8123/database"

# Optional description for the default profile (tooling/AI discovery).
export MCP_CLICKHOUSE_DESCRIPTION="Primary cluster"

# Optional max rows per interactive query (default 500; hard ceiling 1000).
export MCP_CLICKHOUSE_QUERY_MAX_ROWS="500"

# Optional interactive query timeout in seconds (default 30; hard ceiling 300).
export MCP_CLICKHOUSE_QUERY_COMMAND_TIMEOUT_SECONDS="30"

# Optional max rows for snapshot queries (default 10000; hard ceiling 50000).
export MCP_CLICKHOUSE_SNAPSHOT_MAX_ROWS="10000"

# Optional snapshot query timeout in seconds (default 120; hard ceiling 300).
export MCP_CLICKHOUSE_SNAPSHOT_COMMAND_TIMEOUT_SECONDS="120"

多个连接： 使用用户级 config.json 文件（推荐）。环境变量也可以通过 MCP_CLICKHOUSE_PROFILES_<NAME>_ 前缀（例如 MCP_CLICKHOUSE_PROFILES_WAREHOUSE_DSN）生效。

  • Unix 类系统：~/.config/mcp-clickhousex/config.json

  • Windows：%USERPROFILE%\.config\mcp-clickhousex\config.json

示例（config.json）：

{
  "profiles": {
    "default": {
      "dsn": "http://default:@localhost:8123/default",
      "description": "Primary",
      "query_max_rows": 500,
      "query_command_timeout_seconds": 60,
      "snapshot_max_rows": 10000,
      "snapshot_command_timeout_seconds": 120
    },
    "warehouse": {
      "dsn": "http://user:pass@warehouse:8123/analytics",
      "description": "Warehouse"
    }
  }
}

凭据中的特殊字符： 如果用户名或密码包含 URL 保留字符，请在 DSN 中对它们进行百分号编码：

字符

编码

#

%23

?

%3F

/

%2F

@

%40

%

%25

例如，用户名 admin@org 和密码 p#ss? 在 DSN 中变为 admin%40org:p%23ss%3F：http://admin%40org:p%23ss%3F@host:8123/database。

工具

工具描述与 server.py 工具文档字符串一致，只是此处省略了 [ClickHouse] 前缀（该前缀仍保留在 MCP 暴露的元数据中）。参数文本与同一工具上的每个 Field(description=…) 一致。

工具

描述

关键参数

list_profiles

列出已配置的配置文件。每个条目包含名称和可选描述。

—

get_cluster_properties

获取集群属性和执行限制。返回 ClickHouse 服务器版本以及该配置文件的强制限制（最大行数、超时）。

profile — 配置文件名称；省略时使用默认配置文件。来源：profiles。

run_query

执行只读 SELECT 或 WITH … SELECT。每次调用一条语句；拒绝 DML、DDL、SET、SYSTEM 及类似语句。返回 {data, row_count}，其中 data 是 RFC 4180 CSV 字符串。传入 snapshot=true 可将结果持久化到磁盘，并改为接收 {snapshot_uri, row_count}；通过快照资源 URI 获取 CSV。有最大行数上限；超出时设置 truncated 和 row_limit。与 analyze_query 相同的 SQL 校验。

sql（必填）— 只读 SELECT 或 WITH … SELECT。每次调用一条语句；使用限定的 db.table 或 database。参数使用驱动占位符语法。parameters — 驱动占位符的命名参数（例如 %(name)s 或 {name:Type}）。database — 未限定名称时的会话默认数据库。来源：databases。profile — 配置文件名称；省略时使用默认配置文件。来源：profiles。snapshot — 为 true 时，将完整结果持久化为 CSV 文件并返回资源 URI（chx://snapshots/{id}），而不是内联数据。用于可能超过交互式行限制（1 000）的查询。快照限制适用（默认 10 000 行，硬上限 50 000）。条目在 7 天后过期。

run_show

执行 SHOW 内省语句。每次调用一条语句；拒绝 INTO OUTFILE。适用交互式行限制（默认 500，硬上限 1 000）。与 run_query 相同的超时。

sql（必填）— 单条 SHOW 语句（例如 SHOW DATABASES、SHOW CREATE TABLE）。不允许 INTO OUTFILE。parameters — 驱动占位符的命名参数（例如 %(name)s 或 {name:Type}）。database — 未限定名称时的会话默认数据库。来源：databases。profile — 配置文件名称；省略时使用默认配置文件。来源：profiles。

analyze_query

解释只读 SELECT 或 WITH … SELECT。返回 plan、pipeline 和/或 syntax 文本。默认类型为 plan 和 pipeline。使用查询超时和可选数据库；与 run_query 不同，没有最大行数上限。

sql（必填）— 用于 EXPLAIN 的只读 SELECT 或 WITH … SELECT。每次调用一条语句；与 run_query 相同的校验。parameters — 驱动占位符的命名参数（例如 %(name)s 或 {name:Type}）。database — 未限定名称时的会话默认数据库。来源：databases。profile — 配置文件名称；省略时使用默认配置文件。来源：profiles。types — EXPLAIN 变体：plan（索引）、pipeline、syntax。省略时默认为 plan 和 pipeline。

list_databases

列出数据库。返回连接可见的 system.databases 中的行。

profile — 配置文件名称；省略时使用默认配置文件。来源：profiles。

list_tables

列出数据库中的表和视图。返回 system.tables 中的行：name、engine、primary_key、sorting_key、partition_key、total_rows、total_bytes，用于查询规划。

database — 要列出的数据库；省略时使用客户端默认值。来源：databases。profile — 配置文件名称；省略时使用默认配置文件。来源：profiles。

list_columns

列出表或视图的列。返回已解析的数据库和表的 system.columns 中的行。

table（必填）— 表或视图名称，或 database.table。来源：tables。database — 当 table 未限定时使用的数据库；如果 table 包含点则忽略。省略时使用客户端默认值。来源：databases。profile — 配置文件名称；省略时使用默认配置文件。来源：profiles。

资源

服务器通过 URI 可寻址资源（profile 优先的层级结构）暴露与上述工具相同的发现和元数据。每个资源的 description 与对应工具（list_profiles、get_cluster_properties、list_databases、list_tables、list_columns）相匹配，并带有用于 URI 路径参数的 Src: 标签。所有资源内容均为 JSON（application/json），但快照除外，快照返回 CSV（text/csv）。对于默认 profile 或数据库，请使用路径段 default。

资源描述与 server.py 中 @mcp.resource 上的 description=… 一致（与上述相同的省略前缀规则）。

URI

描述

chx://profiles

列出已配置的 profile。每个条目包含名称和可选的描述。

chx://profiles/{profile}/cluster-properties

获取集群属性和执行限制。返回该 profile 的 ClickHouse 服务器版本以及强制限制（最大行数、超时时间）。Src: profiles。

chx://profiles/{profile}/databases

列出数据库。返回连接可见的 system.databases 中的行。Src: profiles。

chx://profiles/{profile}/databases/{database}/tables

列出数据库中的表和视图。返回 system.tables 中的行：name、engine、primary_key、sorting_key、partition_key、total_rows、total_bytes，用于查询规划。Src: profiles, dbs。

chx://profiles/{profile}/databases/{database}/tables/{table}/columns

列出表或视图的列。返回解析后的数据库和表的 system.columns 中的行。Src: profiles, dbs, tables。

chx://snapshots/{id}

按 ID 获取查询结果快照。以 CSV 字符串（表头行 + 数据行）形式返回完整结果。条目在 7 天后过期。Src: run_query with snapshot=true。

安全性

仅允许只读 SQL：run_query 允许 SELECT / WITH … SELECT；run_show 每次调用仅允许一条 SHOW 语句。run_show 不允许使用 INTO OUTFILE。交互式查询强制执行严格的行数上限（默认 500，硬上限 1 000）；对于更大的数据提取，请使用 snapshot=true（默认 10 000，硬上限 50 000）。在驱动允许的情况下支持参数化查询（%(name)s 或 {name:Type} 语法）。使用环境变量存储连接凭据——切勿提交密钥。

MCP 主机示例

使用 uvx mcp-clickhousex 的常见 MCP 客户端代码片段（无需克隆；确保 uv 在您的 PATH 中）。根据需要替换连接信息。

Cursor

{
  "mcpServers": {
    "clickhouse": {
      "command": "uvx",
      "args": ["mcp-clickhousex"],
      "env": {
        "MCP_CLICKHOUSE_DSN": "http://default:@localhost:8123/default"
      }
    }
  }
}

Codex

[mcp_servers.clickhouse]
command = "uvx"
args = ["mcp-clickhousex"]

[mcp_servers.clickhouse.env]
MCP_CLICKHOUSE_DSN = "http://default:@localhost:8123/default"

OpenCode

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "clickhouse": {
      "type": "local",
      "enabled": true,
      "command": ["uvx", "mcp-clickhousex"],
      "environment": {
        "MCP_CLICKHOUSE_DSN": "http://default:@localhost:8123/default"
      }
    }
  }
}

Claude Code

{
  "mcpServers": {
    "clickhouse": {
      "command": "uvx",
      "args": ["mcp-clickhousex"],
      "env": {
        "MCP_CLICKHOUSE_DSN": "http://default:@localhost:8123/default"
      }
    }
  }
}

Copilot

{
  "inputs": [],
  "servers": {
    "clickhouse": {
      "type": "stdio",
      "command": "uvx",
      "args": ["mcp-clickhousex"],
      "env": {
        "MCP_CLICKHOUSE_DSN": "http://default:@localhost:8123/default"
      }
    }
  }
}

配置文件位置： Cursor .cursor/mcp.json，Codex/Copilot/OpenCode 因客户端而异；请参阅您所用客户端的 MCP 文档。

测试

测试需要运行中的 ClickHouse 实例。测试套件会在默认数据库中创建示例表、填充数据，并在测试结束后删除该表。

# Run all tests (unit + functional + e2e)
uv run pytest tests/ -v

测试框架使用 MCP_TEST_CLICKHOUSE_DSN 来定位 ClickHouse 实例。如果未设置，则回退到 http://admin:password123@localhost:8123/default。设置该变量可将测试指向其他服务器，而不会影响您的生产环境 MCP_CLICKHOUSE_DSN：

export MCP_TEST_CLICKHOUSE_DSN="http://user:pass@testhost:8123/default"
uv run pytest tests/ -v

路线图

目前没有计划中的功能。如有改进建议，请提交 issue。

贡献

欢迎提交 issue 或 PR；请遵循现有风格，并在适当的地方添加测试。

许可证

MIT。参见 LICENSE。

Available Tools

8 tools
analyze_queryA
Read-only

[ClickHouse] Explain read-only SELECT or WITH … SELECT.

Returns plan, pipeline, and/or syntax text. Default types plan and pipeline. Uses query timeout and optional database; no max-rows cap unlike run_query.

ParametersJSON Schema
NameRequiredDescriptionDefault
sqlYesRead-only SELECT or WITH … SELECT for EXPLAIN. One statement; same validation as run_query.
typesNoEXPLAIN variants: plan (indexes), pipeline, syntax. Default plan and pipeline if omitted.
profileNoProfile name; uses default profile when omitted. Src: profiles.
databaseNoSession default database for unqualified names. Src: databases.
parametersNoNamed parameters for driver placeholders (e.g. %(name)s or {name:Type}).

Output Schema

ParametersJSON Schema
NameRequiredDescription
planNoEXPLAIN PLAN output.
syntaxNoEXPLAIN SYNTAX output.
pipelineNoEXPLAIN PIPELINE output.

TDQS

A4.6/5.0
Behavior5/5

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

Description adds behavioral context beyond readOnlyHint and openWorldHint annotations, such as query timeout, optional database, and the absence of max-rows cap. No contradiction.

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?

Three concise sentences, front-loaded with core purpose, and each sentence provides distinct information without 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 output schema existence and high parameter coverage, description covers key aspects: purpose, defaults, and comparison. Minor missing details like timeout value are acceptable.

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%, but description adds value by specifying default types (plan and pipeline) and mentioning query timeout, which is not in schema. Slight improvement over baseline.

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 clearly states the tool performs EXPLAIN on read-only SELECT/WITH SELECT, returning plan/pipeline/syntax. Distinguishes from sibling run_query by noting no max-rows cap.

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?

Provides context on when to use (for EXPLAIN) and comparison to run_query. Implicitly limits to read-only queries but lacks explicit alternatives for DDL or other analysis tools.

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

get_cluster_propertiesA
Read-only

[ClickHouse] Get cluster properties and execution limits.

Returns ClickHouse server version plus enforced limits (max rows, timeouts) for the profile.

ParametersJSON Schema
NameRequiredDescriptionDefault
profileNoProfile name; uses default profile when omitted. Src: profiles.

Output Schema

ParametersJSON Schema
NameRequiredDescription
limitsYes
versionYesClickHouse server version string.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, and the description adds context about specific returned data (version, limits). No contradiction. Does not mention any side effects or authorization needs, but read-only nature covers safety.

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, no fluff. First sentence states purpose, second describes output. Information is front-loaded and every sentence adds value.

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?

With an output schema present and simple input, the description provides all necessary context. Annotations cover safety, and the description adequately explains the tool's scope and return content.

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 coverage is 100% and describes the profile parameter well. The description does not add extra details beyond the schema, which is adequate for a single optional parameter.

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 clearly states 'Get cluster properties and execution limits' and specifies it returns 'ClickHouse server version plus enforced limits', which is a specific verb and resource. It distinguishes from sibling tools like run_query and list_profiles.

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?

Implied usage as a read-only check for server properties and limits, but no explicit when-to-use or when-not-to-use guidance compared to siblings like list_profiles.

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

list_columnsA
Read-only

[ClickHouse] List columns for a table or view.

Rows from system.columns for the resolved database and table.

ParametersJSON Schema
NameRequiredDescriptionDefault
tableYesTable or view name, or database.table. Src: tables.
profileNoProfile name; uses default profile when omitted. Src: profiles.
databaseNoDatabase when table is unqualified; ignored if table contains a dot. Client default when omitted. Src: databases.

Output Schema

ParametersJSON Schema
NameRequiredDescription
rowsYesRow values aligned with the columns list.
columnsYesOrdered list of column names. Each row aligns with these names by index.

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint=true, so the description's mention of using system.columns adds some context but does not reveal additional behavioral traits beyond what annotations provide.

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 extremely concise with just two sentences, no redundancy, and the key purpose is front-loaded. Every word adds value.

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?

For a simple read-only list tool with full parameter documentation, an output schema, and clear annotations, the description sufficiently covers the context and functionality without needing to explain return values.

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%, and the tool description does not add any extra meaning beyond the existing parameter descriptions, such as explaining the 'Src' references or providing examples.

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 'List columns for a table or view' with a specific verb and resource. It includes the context '[ClickHouse]' and mentions the data source 'Rows from system.columns', making it distinct from sibling tools like list_tables or list_databases.

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 usage for listing columns of a table or view, but it does not provide explicit guidance on when to use this tool vs alternatives, nor does it mention any prerequisites or exclusions.

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

list_databasesB
Read-only

[ClickHouse] List databases.

Rows from system.databases visible to the connection.

ParametersJSON Schema
NameRequiredDescriptionDefault
profileNoProfile name; uses default profile when omitted. Src: profiles.

Output Schema

ParametersJSON Schema
NameRequiredDescription
rowsYesRow values aligned with the columns list.
columnsYesOrdered list of column names. Each row aligns with these names by index.

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true. Description adds the detail that it queries system.databases and depends on connection visibility. No contradictions with annotations.

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 concise sentences, no wasted words, front-loaded with purpose and context.

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 tool with one optional parameter and an output schema, the description is adequate. Provides source table and visibility context, but could mention output shape briefly.

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 coverage is 100% with parameter 'profile' already documented. Description adds no extra meaning beyond the schema.

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?

Clearly states verb 'List' and resource 'databases', includes context '[ClickHouse]' and source 'system.databases'. Differentiates from siblings like 'list_tables' implicitly but no explicit distinction.

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?

Mentions that rows are from system.databases and visible to the connection, but provides no guidance on when to use this tool vs alternatives like list_tables or run_show. Lacks explicit when-to-use 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.

list_profilesA
Read-only

[ClickHouse] List configured profiles.

Each entry includes name and optional description.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.5/5.0
Behavior3/5

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

The description adds value beyond annotations by specifying that output includes name and optional description. Annotations already declare readOnlyHint=true, so the read-only nature is known. No additional behavioral traits (e.g., ordering, filtering) are disclosed, but the description does not contradict annotations.

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 extremely concise: two sentences that front-load the purpose and follow with a key output detail. Every word earns its place with no redundancy or fluff.

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 zero parameters and the presence of an output schema, the description is mostly complete. It explains what the tool does and what output to expect. It could optionally mention the source of profiles (e.g., system.profiles), but the current level is adequate for a simple listing tool.

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 input schema has no parameters, so schema description coverage is 100%. The description does not need to add parameter semantics. It provides a baseline adequate for a parameterless tool.

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 configured profiles') and the resource ('profiles'). The output details are mentioned (name and optional description). However, it does not explicitly differentiate from sibling list tools (e.g., list_databases, list_tables) beyond the resource name, lacking a contrastive statement.

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. There is no mention of prerequisites, common use cases, or when not to use it. The tool is simple, but the description does not help an agent decide between this and other list tools.

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

list_tablesA
Read-only

[ClickHouse] List tables and views in a database.

Rows from system.tables: name, engine, primary_key, sorting_key, partition_key, total_rows, total_bytes for query planning.

ParametersJSON Schema
NameRequiredDescriptionDefault
profileNoProfile name; uses default profile when omitted. Src: profiles.
databaseNoDatabase to list; client default when omitted. Src: databases.

Output Schema

ParametersJSON Schema
NameRequiredDescription
rowsYesRow values aligned with the columns list.
columnsYesOrdered list of column names. Each row aligns with these names by index.

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, and the description adds context about the specific columns returned. However, it does not disclose any behavioral traits beyond that, but given the annotations, this is adequate.

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?

Extremely concise: two sentences that front-load the purpose and return value. No unnecessary words or repetition.

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 list tool with an output schema and well-documented parameters, the description is nearly complete. A minor gap: it does not clarify behavior when database is omitted (client default), but overall it is sufficient.

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%, so the schema already documents both parameters (profile, database). The description does not add extra meaning beyond what the schema provides, meeting the baseline.

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 lists tables and views in a database, specifying the source (system.tables) and the columns returned. It effectively distinguishes from sibling tools like list_databases and list_columns by focusing on tables.

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 versus alternatives (e.g., run_show or analyze_query). The description merely states functionality without providing context on preferred scenarios or limitations.

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

run_queryA
Read-only

[ClickHouse] Execute read-only SELECT or WITH … SELECT.

One statement; DML, DDL, SET, SYSTEM, and similar are rejected. Max-rows cap; overflow sets truncated and row_limit. Same SQL validation as analyze_query.

Returns {data, row_count} where data is an RFC 4180 CSV string. Pass snapshot=true to persist the result to disk and receive a {snapshot_uri, row_count} instead; fetch the CSV via the snapshot resource URI.

ParametersJSON Schema
NameRequiredDescriptionDefault
sqlYesRead-only SELECT or WITH … SELECT. One statement; use qualified db.table or database. Driver placeholder syntax for parameters.
profileNoProfile name; uses default profile when omitted. Src: profiles.
databaseNoSession default database for unqualified names. Src: databases.
snapshotNoWhen true, persist the full result as a CSV file and return a resource URI (chx://snapshots/{id}) instead of inline data. Use for queries that may exceed the interactive row limit (1 000). Snapshot limits apply (default 10 000 rows, hard ceiling 50 000). Entries expire after 7 days.
parametersNoNamed parameters for driver placeholders (e.g. %(name)s or {name:Type}).

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true and openWorldHint=true. Description aligns fully and adds rich behavioral details: max-rows cap, truncation with row_limit flag, CSV return format, snapshot persistence with expiration and limits. No contradictions.

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?

Description is a single, well-structured paragraph with each sentence serving a distinct purpose: resource and verb, constraints, limits, return format, and snapshot alternative. No fluff.

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?

For a tool with 5 parameters, 100% schema coverage, and an output schema (not shown but indicated), the description covers purpose, constraints, limits, return format, and snapshot behavior comprehensively. No gaps given the context.

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?

Input schema has 100% description coverage, but description adds value by explaining the return format (CSV string and snapshot URI pattern) which is not in the input schema. Also reiterates constraints on sql parameter. Overall meaningfully supplements 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?

Description clearly states it executes read-only SELECT or WITH SELECT on ClickHouse. It specifies the resource ([ClickHouse] queries) and verb (execute read-only). Distinguishes from siblings like run_show and analyze_query by stating specific SQL types and validation.

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 states that only read-only queries are allowed, and DML/DDL/SET etc. are rejected. Mentions same validation as analyze_query, linking to a sibling. Clear context for when to use, but does not explicitly exclude alternatives or provide when-not-to-use guidance.

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

run_showA
Read-only

[ClickHouse] Execute SHOW introspection statement.

One statement per call; INTO OUTFILE rejected. Interactive row limits apply (default 500, hard ceiling 1 000). Same timeout as run_query.

ParametersJSON Schema
NameRequiredDescriptionDefault
sqlYesSingle SHOW statement (e.g. SHOW DATABASES, SHOW CREATE TABLE). No INTO OUTFILE.
profileNoProfile name; uses default profile when omitted. Src: profiles.
databaseNoSession default database for unqualified names. Src: databases.
parametersNoNamed parameters for driver placeholders (e.g. %(name)s or {name:Type}).

Output Schema

ParametersJSON Schema
NameRequiredDescription
rowsYesRow values aligned with the columns list.
columnsYesOrdered list of column names. Each row aligns with these names by index.
row_limitNoThe enforced maximum number of rows returned for this query.
truncatedNoWhether the result set was truncated due to the enforced row limit.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark as read-only, and the description adds critical behavioral details: row limits (500 default, 1000 hard ceiling), INTO OUTFILE rejection, and timeout alignment with run_query. No contradictions.

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?

Three sentences, each earning its place: purpose, constraints on statement, limits. Front-loaded and efficient with zero redundancy.

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?

Given the presence of an output schema, the description sufficiently covers all behavioral aspects for a read-only introspection tool. Includes limits, timeout, and statement restrictions.

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%, so baseline is 3. Description adds value by explaining the sql parameter constraint (single statement, no INTO OUTFILE) and implicitly relates to row limits. Modest but helpful addition.

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 it executes SHOW introspection statements, distinguishing from siblings like run_query. It specifies constraints (single statement, no INTO OUTFILE), making the purpose specific and unambiguous.

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?

Provides clear context for when to use (SHOW statements) and constraints (row limits, timeout). Lacks explicit when-not-to-use alternatives, but the sibling tool names imply run_query for other queries.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 8 tool updatesv0.8.0
    • First observedanalyze_query
    • First observedget_cluster_properties
    • First observedlist_columns
    • First observedlist_databases
    • First observedlist_profiles
    • First observedlist_tables
    • First observedrun_query
    • First observedrun_show
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TDQS

A4/5.0

Scored across 8 tools

Disambiguation5/5

Each tool has a distinct purpose: listing profiles, cluster properties, running SELECT queries, running SHOW statements, analyzing queries, and listing databases, tables, and columns. No overlap in functionality.

Naming Consistency4/5

Uses snake_case consistently, but mixes verb prefixes: 'list_', 'get_', 'run_', 'analyze_'. The pattern is somewhat predictable within categories (metadata listing uses 'list_', execution uses 'run_'), but not fully uniform.

Tool Count5/5

8 tools is well-scoped for a read-only ClickHouse client. Covers metadata discovery, query execution, and analysis without unnecessary tools.

Completeness4/5

Covers essential read-only operations: metadata listing, SELECT, SHOW, and EXPLAIN. Lacks DDL/DML support, but that is intentional. Minor gap: no tool to retrieve table DDL or status.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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