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PostgreSQL MCP Server

by vignesh-codes
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JavaScript
Hybrid
MIT License
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Servidor MCP de PostgreSQL

Un servidor de Protocolo de Contexto de Modelo (MCP) que proporciona acceso a bases de datos PostgreSQL. Este servidor permite a los LLM interactuar con las bases de datos para inspeccionar esquemas, ejecutar consultas y realizar operaciones CRUD (Crear, Leer, Actualizar, Eliminar) en las entradas de la base de datos. Este repositorio es una extensión de PostgreSQL MCP Server, que ofrece funcionalidades para crear tablas, insertar, actualizar, eliminar y eliminar entradas.

Instalación

Para instalar el servidor PostgreSQL MCP, siga estos pasos:

  1. Instalar Docker y Claude Desktop

  2. Clonar el repositorio: git clone https://github.com/vignesh-codes/ai-agents-mcp-pg.git

  3. Ejecutar contenedor PG Docker docker run --name postgres-container -e POSTGRES_USER=admin -e POSTGRES_PASSWORD=admin_password -e POSTGRES_DB=mydatabase -p 5432:5432 -d postgres:latest

  4. Construya el servidor mcp: docker build -t mcp/postgres -f src/Dockerfile .

  5. Abra Claude Desktop y conéctese al servidor MCP actualizando el campo mcpServers en claude_desktop_config.json :

Uso con Claude Desktop

Para usar este servidor con la aplicación Claude Desktop, agregue la siguiente configuración a la sección "mcpServers" de su claude_desktop_config.json :

Estibador

  • Al ejecutar Docker en macOS, utilice host.docker.internal si el servidor se ejecuta en la red del host (por ejemplo, localhost).

  • Se puede agregar un nombre de usuario y una contraseña a la URL de PostgreSQL con postgresql://user:password@host:port/db-name .

{ "mcpServers": { "postgres": { "command": "docker", "args": [ "run", "-i", "--rm", "mcp/postgres", "postgresql://username:password@host.docker.internal:5432/mydatabase" ] } } }

Asegúrese de reiniciar la aplicación de escritorio Claude después de actualizar el archivo de configuración.

Related MCP server: Enhanced PostgreSQL MCP Server

Características añadidas

Funcionalidad existente

  • consulta

    • Ejecutar consultas SQL de solo lectura en la base de datos conectada.

    • Entrada: sql (cadena): la consulta SQL a ejecutar.

    • Todas las consultas se ejecutan dentro de una transacción de SOLO LECTURA.

Nueva funcionalidad

  1. Crear tablas

    • Capacidad de crear nuevas tablas dinámicamente proporcionando un nombre de tabla y definiciones de columnas.

    • Entrada de Claude Desktop:

      { "tableName": "example_table", "columns": [ { "name": "id", "type": "SERIAL PRIMARY KEY" }, { "name": "name", "type": "VARCHAR(255)" }, { "name": "age", "type": "INTEGER" } ] }

  2. Insertar entradas

    • Insertar nuevas entradas en una tabla especificada.

    • Entrada de Claude Desktop:

      { "tableName": "example_table", "values": { "name": "John Doe", "age": 30 } }

  3. Actualizar entradas

    • Actualizar entradas existentes en una tabla según condiciones.

    • Entrada de Claude Desktop:

      { "tableName": "example_table", "values": { "age": 35 }, "conditions": "name = 'John Doe'" }

  4. Eliminar entradas

    • Eliminar entradas específicas en una tabla según las condiciones.

    • Entrada de Claude Desktop:

      { "tableName": "example_table", "conditions": "name = 'John Doe'" }

  5. Tablas de caída

    • Eliminar tablas existentes de la base de datos.

    • Entrada de Claude Desktop:

      { "tableName": "example_table" }

Recursos

El servidor proporciona información de esquema para cada tabla de la base de datos:

  • Esquemas de tabla ( postgres://<host>/<table>/schema )

    • Información del esquema JSON para cada tabla.

    • Incluye nombres de columnas y tipos de datos.

    • Descubierto automáticamente a partir de metadatos de la base de datos.

Muestra

Entrada a Claude Desktop

lets create three tables - users, payments and orders tables. Each table must have a unique id and other required columns. Payments table must have user id as foreign key. Orders table must have payment id as foreign key. Add some sample data to these tables

Salida de Claude Desktop

I'll help you create these three interconnected tables and populate them with sample data. Let's create them one by one. 1. First, let's create the users table: { `columns`: [ { `name`: `id`, `type`: `INTEGER PRIMARY KEY` }, { `name`: `name`, `type`: `TEXT` }, { `name`: `email`, `type`: `TEXT` }, { `name`: `created_at`, `type`: `TEXT` } ], `tableName`: `users` } 2. Now, let's create the payments table with a foreign key reference to users: { `columns`: [ { `name`: `id`, `type`: `INTEGER PRIMARY KEY` }, { `name`: `user_id`, `type`: `INTEGER` }, { `name`: `amount`, `type`: `REAL` }, { `name`: `status`, `type`: `TEXT` }, { `name`: `payment_date`, `type`: `TEXT` } ], `tableName`: `payments` } 3. Finally, let's create the orders table with a foreign key reference to payments: { `columns`: [ { `name`: `id`, `type`: `INTEGER PRIMARY KEY` }, { `name`: `payment_id`, `type`: `INTEGER` }, { `name`: `product_name`, `type`: `TEXT` }, { `name`: `quantity`, `type`: `INTEGER` }, { `name`: `order_date`, `type`: `TEXT` } ], `tableName`: `orders` } Now, let's add some sample data to these tables. First, let's add some users: { `values`: { `id`: `1`, `name`: `John Doe`, `email`: `john@example.com`, `created_at`: `2024-01-01` }, `tableName`: `users` } { `values`: { `id`: `2`, `name`: `Jane Smith`, `email`: `jane@example.com`, `created_at`: `2024-01-05` }, `tableName`: `users` } Now, let's add some payments for these users: { `values`: { `id`: `1`, `amount`: `99.99`, `status`: `completed`, `user_id`: `1`, `payment_date`: `2024-01-10` }, `tableName`: `payments` } { `values`: { `id`: `2`, `amount`: `149.99`, `status`: `completed`, `user_id`: `2`, `payment_date`: `2024-01-12` }, `tableName`: `payments` } Finally, let's add some orders linked to these payments: { `values`: { `id`: `1`, `quantity`: `1`, `order_date`: `2024-01-10`, `payment_id`: `1`, `product_name`: `Laptop` }, `tableName`: `orders` } { `values`: { `id`: `2`, `quantity`: `2`, `order_date`: `2024-01-12`, `payment_id`: `2`, `product_name`: `Smartphone` }, `tableName`: `orders` } Let's verify the data by querying each table: { `sql`: `SELECT * FROM users;` } { `sql`: `SELECT * FROM payments;` } { `sql`: `SELECT * FROM orders;` } Great! We have now created three interconnected tables with sample data. Here's a summary of what we've set up: 1. Users table with basic user information 2. Payments table linked to users through user_id 3. Orders table linked to payments through payment_id The data shows two users who have each made one payment and placed one order. We can now perform various queries to analyze the relationships between these tables. Would you like to see any specific queries or add more data?

Entrada a Claude Desktop

add few more users with IN_PROGRESS and UNSUCCESSFUL payment status

Salida de Claude Desktop

I'll add a few more users with different payment statuses. First, let's add new users: { `values`: { `id`: `3`, `name`: `Mike Johnson`, `email`: `mike@example.com`, `created_at`: `2024-01-08` }, `tableName`: `users` } { `values`: { `id`: `4`, `name`: `Sarah Wilson`, `email`: `sarah@example.com`, `created_at`: `2024-01-09` }, `tableName`: `users` } { `values`: { `id`: `5`, `name`: `Tom Brown`, `email`: `tom@example.com`, `created_at`: `2024-01-11` }, `tableName`: `users` } Now, let's add payments with IN_PROGRESS and UNSUCCESSFUL statuses for these users: { `values`: { `id`: `3`, `amount`: `299.99`, `status`: `IN_PROGRESS`, `user_id`: `3`, `payment_date`: `2024-01-13` }, `tableName`: `payments` } { `values`: { `id`: `4`, `amount`: `199.99`, `status`: `UNSUCCESSFUL`, `user_id`: `4`, `payment_date`: `2024-01-13` }, `tableName`: `payments` } { `values`: { `id`: `4`, `amount`: `199.99`, `status`: `UNSUCCESSFUL`, `user_id`: `4`, `payment_date`: `2024-01-13` }, `tableName`: `payments` } { `values`: { `id`: `5`, `amount`: `399.99`, `status`: `IN_PROGRESS`, `user_id`: `5`, `payment_date`: `2024-01-13` }, `tableName`: `payments` } Let's add orders for the IN_PROGRESS payments (note that we won't add orders for the UNSUCCESSFUL payment): { `values`: { `id`: `3`, `quantity`: `1`, `order_date`: `2024-01-13`, `payment_id`: `3`, `product_name`: `Gaming Console` }, `tableName`: `orders` } { `values`: { `id`: `4`, `quantity`: `1`, `order_date`: `2024-01-13`, `payment_id`: `5`, `product_name`: `4K TV` }, `tableName`: `orders` } Let's verify the data by checking all payments with their status: { `sql`: `SELECT u.name, p.amount, p.status, p.payment_date FROM users u JOIN payments p ON u.id = p.user_id ORDER BY p.payment_date;` } Now we have a good mix of payment statuses in our database: - 2 completed payments (John and Jane) - 2 in-progress payments (Mike and Tom) - 1 unsuccessful payment (Sarah) The orders table only contains entries for completed and in-progress payments, as it makes sense not to create orders for unsuccessful payments. Would you like to see any specific queries or add more data?

Entrada a Claude Desktop

Fetch the users info who have IN_PROGRESS payment status

Salida de Claude Desktop

I'll write a query to fetch user information for those who have payments with IN_PROGRESS status. { `sql`: ` SELECT u.*, p.amount, p.payment_date FROM users u JOIN payments p ON u.id = p.user_id WHERE p.status = 'IN_PROGRESS' ORDER BY u.id; ` } We can see that two users have payments in progress: 1. Mike Johnson (attempting to pay $299.99) 2. Tom Brown (attempting to pay $399.99) Both payments were initiated on January 13, 2024. Would you like to see any additional information about these users or their orders?

Entrada a Claude Desktop

Lets update the payment status to completed for Mike Johnson

Salida de Claude Desktop

I'll update Mike Johnson's payment status from IN_PROGRESS to completed. { `values`: { `status`: `completed` }, `tableName`: `payments`, `conditions`: { `user_id`: `3` } } Let's verify the update by checking all payments again: { `sql`: ` SELECT u.name, p.amount, p.status, p.payment_date FROM users u JOIN payments p ON u.id = p.user_id ORDER BY p.status, p.payment_date; ` } The update was successful. Now we have: - 3 completed payments (John, Jane, and Mike) - 1 in-progress payment (Tom) - 1 unsuccessful payment (Sarah) Would you like to make any other updates to the data?

ENTRADAS DE BD

mydatabase=# SELECT * FROM users; id | name | email | created_at ----+--------------+-------------------+------------ 1 | John Doe | john@example.com | 2024-01-01 2 | Jane Smith | jane@example.com | 2024-01-05 3 | Mike Johnson | mike@example.com | 2024-01-08 4 | Sarah Wilson | sarah@example.com | 2024-01-09 5 | Tom Brown | tom@example.com | 2024-01-11 (5 rows) mydatabase=# SELECT * FROM payments; id | user_id | amount | status | payment_date ----+---------+--------+--------------+-------------- 1 | 1 | 99.99 | completed | 2024-01-10 2 | 2 | 149.99 | completed | 2024-01-12 4 | 4 | 199.99 | UNSUCCESSFUL | 2024-01-13 5 | 5 | 399.99 | IN_PROGRESS | 2024-01-13 3 | 3 | 299.99 | completed | 2024-01-13 (5 rows) mydatabase=# SELECT * FROM orders; id | payment_id | product_name | quantity | order_date ----+------------+----------------+----------+------------ 1 | 1 | Laptop | 1 | 2024-01-10 2 | 2 | Smartphone | 2 | 2024-01-12 3 | 3 | Gaming Console | 1 | 2024-01-13 4 | 5 | 4K TV | 1 | 2024-01-13 (4 rows)

Licencia

Este servidor MCP cuenta con la licencia MIT. Esto significa que puede usar, modificar y distribuir el software libremente, sujeto a los términos y condiciones de la licencia MIT. Para más detalles, consulte el archivo de LICENCIA en el repositorio del proyecto.

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