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MCP Vertica

by nolleh
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Python
Remote

MCP ヴェルティカ

Vertica MCP（モデル・コンテキスト・プロトコル）サーバー

例: MCP サーバー設定

次の内容で、mcp クライアント構成ファイルを作成または編集します。

{
  "mcpServers": {
    "vertica": {
      "command": "uvx",
      "args": [
        "mcp-vertica",
        "--host=localhost",
        "--db-port=5433",
        "--database=VMart",
        "--user=dbadmin",
        "--password=",
        "--connection-limit=10"
      ]
    }
  }
}

[！注記]

  • --sslや--ssl-reject-unauthorizedなどのブールフラグの場合、有効にするにはフラグ (例: "--ssl" ) を追加するだけで、無効にするには省略できます。

  • 空のパスワードの場合は、上記のように空の文字列を使用します。

特徴

データベース接続管理

  • 設定可能な制限を備えた接続プール

  • SSL/TLS サポート

  • 自動接続クリーンアップ

  • 接続タイムアウト処理

クエリ操作

  • SQLクエリを実行する

  • 大規模なクエリ結果をバッチでストリーミングする

  • データコピー操作

  • トランザクション管理

スキーマ管理

  • テーブル構造の検査

  • インデックス管理

  • ビュー管理

  • 制約情報

  • 列の詳細

セキュリティ機能

  • 操作レベルの権限（INSERT、UPDATE、DELETE、DDL）

  • スキーマ固有の権限

  • SSL/TLS サポート

  • ログ内のパスワードマスキング

Related MCP server: MSSQL MCP Server

ツール

データベース操作

  1. execute_query

    • SQLクエリを実行する

    • すべてのSQL操作のサポート

  2. stream_query

    • 大規模なクエリ結果をバッチでストリーミングする

    • 設定可能なバッチサイズ

  3. copy_data

    • COPYコマンドを使用した一括データロード

    • 大規模なデータセットに効率的

スキーマ管理

  1. get_table_structure

    • 詳細なテーブル構造を取得する

    • 列情報

    • 制約

  2. list_indexes

    • テーブルのすべてのインデックスを一覧表示する

    • インデックスの種類と一意性

    • 列情報

  3. list_views

    • スキーマ内のすべてのビューを一覧表示する

    • 定義を表示

構成

環境変数

VERTICA_HOST=localhost
VERTICA_PORT=5433
VERTICA_DATABASE=VMart
VERTICA_USER=newdbadmin
VERTICA_PASSWORD=vertica
VERTICA_CONNECTION_LIMIT=10
VERTICA_SSL=false
VERTICA_SSL_REJECT_UNAUTHORIZED=true

操作権限

ALLOW_INSERT_OPERATION=false
ALLOW_UPDATE_OPERATION=false
ALLOW_DELETE_OPERATION=false
ALLOW_DDL_OPERATION=false

スキーマ権限

SCHEMA_INSERT_PERMISSIONS=schema1:true,schema2:false
SCHEMA_UPDATE_PERMISSIONS=schema1:true,schema2:false
SCHEMA_DELETE_PERMISSIONS=schema1:true,schema2:false
SCHEMA_DDL_PERMISSIONS=schema1:true,schema2:false

インストール

uvx mcp-vertica

ライセンス

このプロジェクトは MIT ライセンスに基づいてライセンスされています - 詳細については LICENSE ファイルを参照してください。

Docker環境で実行

Docker Compose を使用して Vertica を実行する場合、次のように MCP サーバーを実行できます。

1. 直接パラメータで実行

uvx mcp-vertica \
  --host localhost \
  --db-port 5433 \
  --database VMart \
  --user dbadmin \
  --password "" \
  --connection-limit 10

2. 環境変数を使って実行する

次の内容の.envファイルを作成します。

VERTICA_HOST=localhost
VERTICA_PORT=5433
VERTICA_DATABASE=test_db
VERTICA_USER=test_user
VERTICA_PASSWORD=test_password
VERTICA_CONNECTION_LIMIT=10
VERTICA_SSL=false
VERTICA_SSL_REJECT_UNAUTHORIZED=true

次に.envで実行します

uvx mcp-vertica \
  --env-file .env

テスト用、VerticaDB Docker Compose の例

version: "3.8"

services:
  vertica:
    # image: vertica/vertica-ce:11.1.0-0
    image: vertica/vertica-ce:latest
    platform: linux/amd64
    container_name: vertica-ce
    environment:
      VERTICA_MEMDEBUG: 2
    ports:
      - "5433:5433"
      - "5444:5444"
    volumes:
      - vertica_data:/home/dbadmin/VMart
    healthcheck:
      test:
        [
          "CMD",
          "/opt/vertica/bin/vsql",
          "-h",
          "localhost",
          "-d",
          "VMart",
          "-U",
          "dbadmin",
          "-c",
          "SELECT 1",
        ]
      interval: 10s
      timeout: 5s
      retries: 5
      start_period: 30s
    restart: unless-stopped

volumes:
  vertica_data:
    driver: local

Available Tools

6 tools
copy_dataC

Copy data into a Vertica table using COPY command.

Args:
    ctx: FastMCP context for progress reporting and logging
    schema: vertica schema to execute the copy against
    table: Target table name
    data: List of rows to insert

Returns:
    Status message indicating success or failure
ParametersJSON Schema
NameRequiredDescriptionDefault
schemaYes
tableYes
dataYes

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It mentions using COPY command but lacks details on permissions, error handling, or side effects. Returns a status message but no specifics.

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?

Description is concise with Args and Returns sections, front-loading the purpose. No unnecessary sentences.

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 no output schema, no annotations, and 3 required params, the description is incomplete. It doesn't mention table existence requirements, data format constraints, or behavior on conflict.

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%, but description adds minimal meaning: 'vertica schema', 'Target table name', 'List of rows to insert'. The 'data' parameter lacks structure details beyond list of rows, leaving ambiguity.

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 it copies data into a Vertica table using COPY command, which is a specific verb and resource. It is easily distinguishable from siblings like execute_query or list_indexes.

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 like execute_query for single inserts. No prerequisites or exclusions are mentioned.

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

execute_queryC

Execute a SQL query and return the results.

Args:
    ctx: FastMCP context for progress reporting and logging
    query: SQL query to execute
    database: Optional database name to execute the query against

Returns:
    Query results as a string
ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only states the action and return type, omitting crucial details such as whether the query is read-only, impacts on data, or required permissions.

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 reasonably concise with a clear structure (Args, Returns). The purpose sentence is front-loaded, and every sentence serves a purpose despite the parameter mismatch.

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 that there is no output schema and no annotations, the description is insufficient. It lacks details about error handling, supported SQL syntax, database selection, and whether the tool is safe for read-only queries.

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?

The description adds meaning for the 'query' parameter ('SQL query to execute'), but it also mentions 'ctx' and 'database' which are not in the input schema, causing confusion. Schema description coverage is 0%, so the description should compensate but instead introduces inconsistency.

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 'Execute a SQL query and return the results,' which is a specific verb and resource. However, the mention of parameters not present in the input schema (ctx, database) slightly reduces clarity.

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 siblings like stream_query or copy_data. The description does not specify prerequisites or alternatives.

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

get_table_structureB

Get the structure of a table including columns, data types, and constraints.

Args:
    ctx: FastMCP context for progress reporting and logging
    table_name: Name of the table to inspect
    schema: Schema name (default: public)

Returns:
    Table structure information as a string
ParametersJSON Schema
NameRequiredDescriptionDefault
table_nameYes
schemaNopublic

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It mentions returning 'Table structure information as a string' but does not describe the format, side effects (e.g., read-only), error behavior, or performance characteristics.

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 relatively concise, with the purpose stated in the first line. However, the Args/Returns block adds some verbosity without significant extra value, and could be streamlined.

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 no output schema and a potentially complex return value, the description should elaborate on the format of the returned string (e.g., JSON, plain text). It also lacks error handling details and examples.

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 0%, so the description adds value beyond the schema. It defines table_name and schema with a default, but does not provide examples, constraints (e.g., required format for table_name), or clarification of schema parameter semantics.

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 retrieves table structure including columns, data types, and constraints. It uses a specific verb (Get) and resource (table structure), and is distinct from sibling tools like execute_query or list_views.

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 does not provide any guidance on when to use this tool versus alternatives. No mention of prerequisites, cases where other tools are preferred, or scope limitations.

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

list_indexesB

List all indexes for a specific table.

Args:
    ctx: FastMCP context for progress reporting and logging
    table_name: Name of the table to inspect
    schema: Schema name (default: public)

Returns:
    Index information as a string
ParametersJSON Schema
NameRequiredDescriptionDefault
table_nameYes
schemaNopublic

TDQS

B3/5.0
Behavior2/5

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

No annotations are present, so the description must disclose behavioral traits. It states returns are a string but omits details on performance, side effects, permissions, or error handling, leaving the agent under-informed.

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 short and includes an Args/Returns structure, making it reasonably scannable. It could be slightly more concise by merging the header, but overall it is efficient.

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 tool has 2 parameters and no output schema, the description is minimal. It lacks details on the return format, edge cases, or database prerequisites, making it only barely adequate for operation.

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 0%, but the description adds meaningful parameter descriptions ('Name of the table to inspect' and 'Schema name (default: public)'), compensating for the lack of schema descriptions. This adds value 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?

The description clearly states 'List all indexes for a specific table,' specifying the verb and resource. However, it does not differentiate from sibling tools like get_table_structure, which might have similar functionality.

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 alternative tools. The description only states what the tool does, without any when-not or alternative references.

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

list_viewsB

List all views in a schema.

Args:
    ctx: FastMCP context for progress reporting and logging
    schema: Schema name (default: public)

Returns:
    View information as a string
ParametersJSON Schema
NameRequiredDescriptionDefault
schemaNopublic

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions returning a string but does not reveal side effects, authentication needs, or performance implications. The included 'ctx' parameter is not in the input schema, causing inconsistency.

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 short and uses a structured 'Args/Returns' format. However, it includes redundant technical formatting and a parameter (ctx) that does not appear in the schema, which could confuse an agent.

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?

Missing important details: the return format of the string, progress reporting behavior (despite mentioning ctx), and how to handle large results. The discrepancy between description params and schema further reduces completeness.

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 description coverage is 0% (low), so the description must compensate. The description provides meaning for the 'schema' parameter ('Schema name (default: public)'), adding semantic value beyond the schema's default and type. However, it includes an undocumented 'ctx' parameter, slightly reducing clarity.

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 explicitly states 'List all views in a schema,' clearly identifying the resource (views) and action (list). It distinguishes from sibling tools like list_indexes and get_table_structure by specifying it is for views.

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. It does not mention prerequisites, exclusions, or comparison with siblings. The description only states what it does, not the context for use.

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

stream_queryC

Execute a SQL query and return the results in batches as a single string.

Args:
    ctx: FastMCP context for progress reporting and logging
    query: SQL query to execute
    batch_size: Number of rows to fetch at once

Returns:
    Query results as a concatenated string
ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
batch_sizeNo

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description should fully disclose behavioral traits. It mentions batching and progress reporting but omits critical details like whether the tool modifies data, safety concerns, or authentication requirements. The description does not warn about potentially destructive SQL operations.

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 concise with a single-purpose summary and structured Args/Returns. No extraneous text, though it could be more informative without losing conciseness.

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 tool's complexity (SQL execution with optional batching, no output schema) and zero annotations, the description is incomplete. It fails to explain return value format, error handling, or when to adjust batch_size. The agent lacks sufficient context to use it safely.

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%, so the description must add meaning. It provides minimal descriptions for 'query' and 'batch_size' (e.g., 'SQL query to execute') but lacks constraints, valid ranges, or examples. The batch_size default and meaning are implied but not elaborated.

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 ('Execute a SQL query') and the unique output format ('return the results in batches as a single string'). This distinguishes it from siblings like execute_query, which likely returns results differently.

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 (e.g., execute_query). There is no mention of prerequisites, limitations, or exclusions.

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. Dates show when Glama detected each change.

  1. 6 tool updates
    • First observedcopy_data
    • First observedexecute_query
    • First observedget_table_structure
    • First observedlist_indexes
    • First observedlist_views
    • First observedstream_query
Install Server
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TDQS

B3.1/5.0
Disambiguation3/5

Most tools are distinct, but 'execute_query' and 'stream_query' both execute SQL queries with only a difference in batch handling, leading to potential confusion for an agent.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with underscores (e.g., copy_data, list_indexes, get_table_structure), making the naming predictable.

Tool Count4/5

6 tools is a reasonable size for a focused database server, though it leans slightly low.

Completeness2/5

The set covers query execution and data copying but lacks essential operations like table creation, modification, and deletion, leaving significant gaps for typical database management.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

Unclaimed servers have limited discoverability.

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