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Local Pgsql MCP Server

@z-waterking

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

z-waterking

提交者

px zater

关于 Local Pgsql MCP Server

一个本地访问PGSQL的MCP Server

#database#analysis#pgsql

Local Pgsql MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "github": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp-pgsql-python-service",
        ".",
        "&&",
        "docker",
        "run",
        "-p",
        "8000:8000",
        "-e",
        "DB_HOST=${DB_HOST}",
        "-e",
        "DB_PORT=${DB_PORT:-5432}",
        "-e",
        "DB_NAME=${DB_NAME}",
        "-e",
        "DB_USER=${DB_USER}",
        "-e",
        "DB_PASSWORD=${DB_PASSWORD}",
        "mcp-pgsql-python-service"
      ],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "YOUR_GITHUB_TOKEN",
        "DB_HOST": "postgres",
        "DB_PORT": "5432",
        "DB_NAME": "postgres",
        "DB_USER": "postgres",
        "DB_PASSWORD": "postgres"
      }
    }
  }
}

Local Pgsql MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is local_pgsql?

local_pgsql is a database analytics and query automation toolkit that provides structured data access for analysis, reporting, and AI-augmented workflows. It is designed for developers and data analysts who need to explore PostgreSQL databases, run parameterized SQL queries, and perform statistical analysis through a modular tool interface.

How to use local_pgsql?

Initialize the MCP with a database connection string, register tools and prompts using the provided API, then call any of the built-in tools or prompts by name. For example, register a DatabaseManager for a PostgreSQL URI and enable tools such as list_tables, run_query, or get_summary_statistics.

Key features of local_pgsql

  • List all tables and get their schemas
  • Preview table contents with data sampling
  • Execute parameterized SQL queries
  • Compute numerical summaries and correlation matrices
  • Perform group-by aggregations with multiple functions
  • Run temporal aggregation and anomaly detection

Use cases of local_pgsql

  • Data exploration to rapidly understand dataset structure and content
  • Automated reporting with scheduled statistical summaries
  • Anomaly monitoring for real-time data quality checks
  • AI-augmented analysis via structured data access for LLMs

常见问题

1

What database systems does local_pgsql support?

The toolkit includes a `DatabaseManager` interface for backend-agnostic operations, and the integration example shows a PostgreSQL connection string.

2

What tools are available for statistical analysis?

Tools include `get_summary_statistics` (mean, standard deviation), `analyze_correlations` (correlation matrices), and `group_by_analysis` (multi-function aggregations).

3

Does local_pgsql include built-in prompts?

Yes, it provides a basic SQL guide (`basic_sql_guide`) and analysis task templates (`data_analysis_tasks`).

4

How are tools registered and invoked?

Tools are dynamically registered via the `@mcp.tool` decorator and called using `mcp.call_tool` with the tool name and parameters.

5

What type of anomaly detection is supported?

It offers Z-score and IQR based anomaly detection through the `detect_anomalies` tool.

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