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mysqldb-mcp-server

by burakdirin
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Python
Remote

Servidor MCP mysqldb-mcp-server

insignia de herrería

Un proyecto de servidor MCP de base de datos MySQL.

Instalación

Puedes instalar el paquete usando uv :

uv pip install mysqldb-mcp-server

O usando pip :

pip install mysqldb-mcp-server

Related MCP server: MySQL Custom MCP Server

Componentes

Herramientas

El servidor proporciona dos herramientas:

  • connect_database : se conecta a una base de datos MySQL específica

    • parámetro database : Nombre de la base de datos a la que conectarse (cadena)

    • Devuelve un mensaje de confirmación cuando la conexión es exitosa

  • execute_query : ejecuta consultas MySQL

    • parámetro query : consulta/consultas SQL a ejecutar (cadena)

    • Devuelve los resultados de la consulta en formato JSON

    • Se pueden enviar múltiples consultas separadas por punto y coma

Configuración

El servidor utiliza las siguientes variables de entorno:

  • MYSQL_HOST : Dirección del servidor MySQL (predeterminado: "localhost")

  • MYSQL_USER : nombre de usuario de MySQL (predeterminado: "root")

  • MYSQL_PASSWORD : Contraseña de MySQL (predeterminada: "")

  • MYSQL_DATABASE : Base de datos inicial (opcional)

  • MYSQL_READONLY : modo de solo lectura (establecido en 1/verdadero para habilitar, valor predeterminado: falso)

Inicio rápido

Instalación

Escritorio de Claude

MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

Ventanas: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "mysqldb-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/burakdirin/Projects/mysqldb-mcp-server",
        "run",
        "mysqldb-mcp-server"
      ],
      "env": {
        "MYSQL_HOST": "localhost",
        "MYSQL_USER": "root",
        "MYSQL_PASSWORD": "password",
        "MYSQL_DATABASE": "[optional]",
        "MYSQL_READONLY": "true"
      }
    }
  }
}
{
  "mcpServers": {
    "mysqldb-mcp-server": {
      "command": "uvx",
      "args": [
        "mysqldb-mcp-server"
      ],
      "env": {
        "MYSQL_HOST": "localhost",
        "MYSQL_USER": "root",
        "MYSQL_PASSWORD": "password",
        "MYSQL_DATABASE": "[optional]",
        "MYSQL_READONLY": "true"
      }
    }
  }
}

Instalación mediante herrería

Para instalar MySQL Database Integration Server para Claude Desktop automáticamente a través de Smithery :

npx -y @smithery/cli install @burakdirin/mysqldb-mcp-server --client claude

Desarrollo

Construcción y publicación

Para preparar el paquete para su distribución:

  1. Sincronizar dependencias y actualizar archivo de bloqueo:

uv sync

  1. Distribuciones de paquetes de compilación:

uv build

Esto creará distribuciones de origen y de rueda en el directorio dist/ .

  1. Publicar en PyPI:

uv publish

Nota: Deberás configurar las credenciales de PyPI a través de variables de entorno o indicadores de comando:

  • Token: --token o UV_PUBLISH_TOKEN

  • O nombre de usuario/contraseña: --username / UV_PUBLISH_USERNAME y --password / UV_PUBLISH_PASSWORD

Depuración

Dado que los servidores MCP se ejecutan en stdio, la depuración puede ser complicada. Para una experiencia óptima, recomendamos usar el Inspector MCP .

Puede iniciar el Inspector MCP a través de npm con este comando:

npx @modelcontextprotocol/inspector uv --directory /Users/burakdirin/Projects/mysqldb-mcp-server run mysqldb-mcp-server

Al iniciarse, el Inspector mostrará una URL a la que podrá acceder en su navegador para comenzar a depurar.

Available Tools

2 tools
connect_databaseC

Connect to a specific MySQL database

ParametersJSON Schema
NameRequiredDescriptionDefault
databaseYes

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the action but doesn't disclose behavioral traits like whether this establishes a persistent connection, requires authentication, has rate limits, or what happens on failure. For a connection tool with zero annotation coverage, this leaves critical operational details unspecified.

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, clear sentence with no wasted words, making it easy to parse and front-loaded with essential information. Every word earns its place by specifying the action and target.

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 (establishing a database connection), lack of annotations, no output schema, and low schema coverage, the description is insufficient. It doesn't cover what the tool returns, error conditions, or dependencies with the sibling 'execute_query' tool, leaving too many gaps for effective use.

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 description coverage is 0%, and the description adds no parameter information beyond implying a 'database' parameter exists. It doesn't explain what the 'database' parameter represents (e.g., database name, connection string), valid values, or format, failing to compensate for the schema's lack of descriptions.

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 ('Connect to') and target resource ('a specific MySQL database'), making the purpose immediately understandable. It doesn't explicitly distinguish from the sibling 'execute_query' tool, but the verb 'connect' versus 'execute' implies different operations.

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, prerequisites, or contextual constraints. With a sibling tool 'execute_query' available, there's no indication of whether connection must precede query execution or if they can be used independently.

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

execute_queryC

Execute MySQL queries

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes

TDQS

C2.1/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails to do so. It doesn't mention whether this is a read-only or destructive operation, authentication requirements, error handling, rate limits, or what the response looks like. For a database query tool with zero annotation coverage, this is a critical gap in transparency.

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 three words, front-loaded and free of unnecessary information. Every word ('Execute MySQL queries') directly contributes to the core purpose, making it efficient in structure, though this brevity contributes to gaps in other dimensions.

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

Completeness1/5

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

Given the complexity of a database query tool, lack of annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It fails to address key aspects like behavioral traits, parameter details, return values, or usage context, making it insufficient for effective agent tool invocation.

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

Parameters1/5

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

The schema description coverage is 0%, meaning the input schema provides no descriptions for the 'query' parameter. The description 'Execute MySQL queries' adds no meaningful semantics beyond the parameter name—it doesn't explain the expected format, syntax, constraints, or examples for the query. This leaves the parameter entirely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Execute MySQL queries' clearly states the verb ('execute') and resource ('MySQL queries'), making the purpose understandable. However, it lacks specificity about what types of queries are supported (e.g., SELECT, INSERT, UPDATE) and doesn't distinguish from the sibling tool 'connect_database', which appears to be a different operation. This makes it vague but not tautological.

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 'connect_database' or other alternatives. It doesn't mention prerequisites (e.g., whether a database connection must be established first), use cases, or exclusions. This leaves the agent with no contextual direction for tool selection.

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. 2 tool updatesv1.0.0
    • First observedconnect_database
    • First observedexecute_query
Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

C2.7/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: connect_database handles database connections, while execute_query handles query execution. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool based on the task.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern (connect_database and execute_query), using snake_case throughout. This predictable naming scheme enhances readability and reduces confusion for agents interacting with the server.

Tool Count2/5

With only 2 tools, the server feels under-scoped for a MySQL database management system. Core operations like creating tables, inserting data, or managing schemas are missing, which limits its utility for typical database workflows. This count is too low for the apparent domain.

Completeness2/5

The tool surface is severely incomplete for MySQL database operations. While connecting and executing queries are foundational, there are significant gaps in CRUD operations (e.g., no create, read, update, or delete tools), schema management, or data manipulation, which will likely cause agent failures in real-world scenarios.

Maintenance

ActivityInactive
ResponsivenessNo issues

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