"Vector Database" matching MCP servers:

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

Enables any MCP client to index files, directories, and arbitrary text into a local SQLite-backed vector database and perform semantic search with language-aware chunking, filters, and context expansion, all offline without network calls.

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.

Enables agents to optimize and clean SVG vector paths, rasterize SVGs into crisp sub-pixel PNGs at custom DPI with alpha preserved, generate high-error-correction vector QR codes for payment URIs, and compress images to WebP while stripping EXIF metadata. Tools are metered via x402 USDC micropayments on Base L2.

A SQL Server CLI and MCP server for Claude Code that supports standard SQL Server authentication for database interaction and management. It enables users to perform schema exploration, execute queries, and manage data records with built-in SQL injection prevention.

Offline PostgreSQL diagnostics: reviews SQL, risky migrations, candidate indexes and EXPLAIN JSON plans without database credentials or executing statements.

A database MCP server providing 33 tools across PostgreSQL, MySQL, and SQLite, with connection groups, rollback, dump/restore, and schema auto-discovery via natural language.

A Model Context Protocol server that enables semantic search capabilities by providing tools to manage Qdrant vector database collections, process and embed documents using various embedding services, and perform semantic searches across vector embeddings.

Enables interaction with Cloudflare D1 databases through natural language by providing tools to list tables and execute SQL queries. Uses Cloudflare's REST API for lightweight database operations without requiring direct database connections.

Enables AI agents to securely interact with multiple databases (MySQL, PostgreSQL) via natural language queries, with cross-database querying and enterprise-grade security.

MCP server for unified SQL database access, supporting multiple databases with schema discovery, caching, and safety controls.

A Model Context Protocol server for unified database access and management, supporting multiple databases with CRUD operations, transactions, metadata queries, and built-in security features.

Enables AI agents to query and explore PostgreSQL and MySQL clusters from a single main configuration, with dynamic per-database routing, automatic database discovery and sync, table/schema inspection, and hierarchical write-rule protection that can block or allow specific SQL mutation operations.

Enables AI applications to discover MySQL and PostgreSQL database schemas and run validated read-only SELECT queries against a configured database, with result limits and SQL safety controls.

Provides AI assistants with read-only access to inspect database schemas, preview data, and run safe queries across PostgreSQL, MySQL, MongoDB, and SQL Server. It enables AI tools to understand database structures and relationships automatically to generate more accurate code.

Enables querying a curated book database using MCP tools to retrieve basic or detailed book information by ISBN or title, including batch lookups.

An MCP server that scans your codebase to automatically generate comprehensive database documentation from your models, entities, migrations, and schema files.

Gives multiple AI coding agents a shared, persistent memory by indexing your code and documentation into a vector database with AST-aware chunking and hybrid semantic/keyword search. Agents can search across projects and store, update, or forget decisions, conventions and lessons learned, all self-hosted with local embeddings.

Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.

An extensible MCP server for database operations that supports PostgreSQL for managing schemas, tables, data, and user permissions. It features automatic migration recording for DDL changes and integrates with various AI-powered editors like Cursor, Zed, and Claude Code.

Enables AI assistants to query PDF documents by ingesting them into a vector database and generating answers grounded in the actual documents.

A modular MCP server that enables interaction with multiple database types including PostgreSQL, MySQL, SQLite, Redis, MongoDB, and LDAP. It provides tools for executing queries, managing SQL commands, and exploring database schemas with configurable read-only security.

MCP to index techincal docs on local vector database to work with Cursor

Enables AI assistants to interact with and manage multiple database types (PostgreSQL, MySQL, SQLite, SQL Server, MongoDB, Redis) through natural language, supporting query analysis, schema management, data analysis, backup/restore, and security analysis.

Provides a natural language interface for querying and managing PostgreSQL, MySQL, MariaDB, MSSQL, and SQLite databases using the Model Context Protocol. Users can explore database schemas and visualize query results through an integrated web dashboard.

This server provides database access capabilities to Claude, supporting SQLite, SQL Server, PostgreSQL, and MySQL databases.

A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.

In-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.

An MCP server that analyzes SQL schemas, generates realistic test data, benchmarks queries, and provides optimization recommendations to improve database performance.

Enables AI assistants to interact with PostgreSQL and Supabase databases through natural language. Supports secure database operations including queries, migrations, and schema management with user-provided credentials.