Model Context Protocol server for PostgreSQL vector database management with pgvector extension
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# pgvector MCP Server 一个基于 Model Context Protocol (MCP) 的 PostgreSQL 向量数据库管理服务器,专为现代AI应用设计。 ## 功能特性 - **MCP 兼容**: 完全基于 Model Context Protocol,与AI助手无缝集成 - **集合管理**: 创建、列出、重命名和删除向量集合 - **向量操作**: 添加向量、搜索相似内容、批量文档处理 - **智能编码**: 自动检测文件编码,特别优化Windows中文文件兼容性 - **嵌入服务**: 集成阿里云DashScope text-embedding-v4模型 - **现代包管理**: 基于uv包管理器,快速安装和依赖管理 - **原子操作**: 数据库事务保证集合重命名等操作的原子性 - **跨平台支持**: Windows、macOS、Linux全平台兼容 ## 快速开始 ### 1. 安装方式 **方式1:使用 uvx 直接运行 (最推荐)** ```bash # 无需安装,直接在MCP配置中使用uvx运行 # uvx会自动下载和管理包 ``` **方式2:使用 uv 安装** ```bash # 全局工具安装 uv tool install pgvector-mcp-server # 或项目依赖安装 uv add pgvector-mcp-server ``` **方式3:使用 pip 安装** ```bash pip install pgvector-mcp-server ``` ### 2. 设置数据库 ```bash # 连接PostgreSQL并启用pgvector扩展 psql postgres -c "CREATE EXTENSION IF NOT EXISTS vector;" # 创建专用数据库(可选) createdb mcp_vectors ``` ### 3. 配置MCP客户端 在你的MCP客户端配置文件中添加以下配置 (例如 Claude Desktop): **推荐配置 (使用 uvx,无需预安装)**: ```json { "mcpServers": { "pgvector-mcp-server": { "command": "uvx", "args": ["pgvector-mcp-server"], "env": { "DATABASE_URL": "postgresql://username:password@localhost:5432/mcp_vectors", "DASHSCOPE_API_KEY": "your_dashscope_api_key_here", "DEBUG": "false" } } } } ``` **备选配置 (如果已安装)**: ```json { "mcpServers": { "pgvector-mcp-server": { "command": "pgvector-mcp-server", "env": { "DATABASE_URL": "postgresql://username:password@localhost:5432/mcp_vectors", "DASHSCOPE_API_KEY": "your_dashscope_api_key_here", "DEBUG": "false" } } } } ``` **传统配置 (使用 Python 模块)**: ```json { "mcpServers": { "pgvector-mcp-server": { "command": "python", "args": ["-m", "pgvector_mcp_server"], "env": { "DATABASE_URL": "postgresql://username:password@localhost:5432/mcp_vectors", "DASHSCOPE_API_KEY": "your_dashscope_api_key_here", "DEBUG": "false" } } } } ``` ### 4. 验证安装 使用MCP客户端调用 `status` 工具验证连接: ```json { "tool": "st…
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