Is the server read‑only by default?
Yes. Write operations (INSERT, UPDATE, DELETE) are blocked unless the `ALLOW_WRITE_OPERATIONS` environment variable is set to `true`.
@JaviMaligno
基本信息
MCP server with 14 tools for PostgreSQL database operations. Query databases, explore schemas, analyze tables, list indexes/constraints, and get performance statistics. Features security-first design with SQL injection prevention and read-only mode by default. Works with Claude D
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"postgres": {
"command": "postgresql-mcp",
"env": {
"POSTGRES_HOST": "localhost",
"POSTGRES_PORT": "5432",
"POSTGRES_USER": "your-user",
"POSTGRES_PASSWORD": "your-password",
"POSTGRES_DB": "your-database"
}
}
}
}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。
MCP Server for PostgreSQL is a Model Context Protocol server that enables AI assistants to interact with PostgreSQL databases. It provides tools for query execution, schema exploration, performance analysis, and documentation generation, and it works with any MCP-compatible client such as Claude Code or Claude Desktop.
Install via pipx install postgresql-mcp or pip install postgresql-mcp. Configure by setting environment variables like POSTGRES_HOST, POSTGRES_USER, POSTGRES_PASSWORD, and POSTGRES_DB (with POSTGRES_PORT, POSTGRES_SSLMODE, ALLOW_WRITE_OPERATIONS, QUERY_TIMEOUT, and MAX_ROWS as optional). Then add to a client using a command like claude mcp add postgres -s user -e ... -- postgresql-mcp.
Yes. Write operations (INSERT, UPDATE, DELETE) are blocked unless the `ALLOW_WRITE_OPERATIONS` environment variable is set to `true`.
Python 3.10 or later is required. For development, `uv` and a PostgreSQL instance are needed; production use only needs the installed package.
Data remains in the PostgreSQL database that the server connects to. The server does not store any data locally.
Yes. By default, a maximum of 1000 rows is returned (`MAX_ROWS`), and queries time out after 30 seconds (`QUERY_TIMEOUT`). These can be configured via environment variables.
The server connects to PostgreSQL using credentials provided as environment variables (`POSTGRES_USER`, `POSTGRES_PASSWORD`). Passwords are stored using Pydantic’s `SecretStr` and never appear in logs or error messages.

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