"Overview and Information on PG Vector" matching MCP servers:

A production-grade MCP server for integrating RAG into AI agents, supporting multiple vector databases with enterprise security and dynamic tool selection.

A shared, persistent MCP memory server for coding agents that enables storing and retrieving project decisions and context across different tools like Claude Code, Codex, and Cursor using semantic vector search.

Integrates RAG into AI agents via MCP Server, supporting multiple vector database technologies for collection management and search operations.

Enables integrating RAG into AI agents via MCP server, supporting multiple vector database technologies.

Enables AI assistants to query PostgreSQL databases, inspect schemas, and retrieve complete DDL with built-in read-only protection. It supports multiple database connections and allows for secure database interaction and exploration via the Model Context Protocol.

A lightweight Postgres MCP server for safe database exploration and query analysis, read-only by default, with multi-database support.

Enables semantic search across PostgreSQL, TimescaleDB, and PostGIS documentation to help AI coding assistants write better PostgreSQL code.

AI-native PostgreSQL health checker with 26 MCP tools for query analysis, bloat detection, migration safety, and CI integration.

PostgreSQL MCP server that converts natural language to SQL and executes queries, with multi-database support and robust read-only safety checks.

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

A secure PostgreSQL Model Context Protocol server that provides read-only database access through tools like schema listing, object inspection, query execution, and EXPLAIN analysis, with database-enforced access control via read-only transactions and a minimal role rather than SQL text parsing.

MCP server for OpenAI Vector Store API, managing vector stores, files, file batches, and semantic search.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

Turns your Readwise library into a blazing-fast semantic search engine with a streaming MCP server for LLM clients, supporting vector search, nightly syncs, and deployment on serverless platforms like Vercel.

Securely connect AI assistants to PostgreSQL databases with read-only access, schema discovery, querying, and performance analysis tools.

Provides AI coding agents with persistent, long-term memory through local semantic search and SQLite storage. It enables agents to save and retrieve architectural decisions or project context across different conversation sessions without requiring cloud services.

A PostgreSQL MCP server that enables querying and managing multiple databases through a single configuration file without needing separate server instances. It provides tools for executing SQL queries, listing databases, and inspecting table schemas with built-in support for read-only transactions and connection pooling.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

Provides comprehensive management of OpenAI Vector Stores, allowing AI assistants to upload files, manage vector databases, and handle batch operations via the OpenAI API. It supports multiple deployment methods, including Cloudflare Workers and local NPM installation, for seamless integration with MCP-compatible clients.