"Vector Database" matching MCP servers:

A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.

Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.

Enables AI agents to interact with an embedded graph database (GrafeoDB) via the Model Context Protocol, providing tools for graph CRUD, GQL queries, full-text and vector search, and graph algorithms.

Enables LLMs to interact with Zvec vector database through tools for collection management, document operations, vector search, and AI-powered embeddings.

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

Enables agents to track causal relationships, reconcile concurrent state changes, and coordinate consensus across distributed networks using vector clocks, CRDTs, gossip, and quorum-based protocols.

An example server that enables interaction with Alibaba Cloud's Lindorm multi-model NoSQL database, allowing applications to perform vector searches, full-text searches, and SQL operations through a unified interface.

Enables simulation of multi-qubit quantum circuits using complex state vectors, including unitary gates, entanglement, Born-rule measurement sampling, state fidelity, and probability distributions via MCP.

Enables LLMs to interact with Rememberizer Vector Store for semantic search, document creation, deletion, and modification.

Enables natural language querying of MongoDB data by transforming AI agent questions into MongoDB aggregations. Supports secure data separation, semantic vector search, and advanced lookup capabilities for database interactions.

Official MCP server for Stoolap, an embedded SQL database written in Rust. Lets assistants run SQL queries and transactions, inspect and change schemas, and do vector search over a local file or in-memory database, with a read-only mode.

Lets coding agents search a local Markdown docs folder, ask questions answered with linked source passages, and add or replace pages. Backed by Postgres full-text search with no vector database required.

A Model Context Protocol server that enables LLMs like Claude to interact with SQLite and SQL Server databases, allowing for schema inspection and SQL query execution.

Enables interaction with KDB.AI through natural language for vector database operations, similarity searches, hybrid search, and advanced data analysis.

Enables RAG-powered documentation search using OpenAI embeddings and Pinecone vector database. Provides an extensible framework for adding additional tools with support for both local STDIO and production HTTP transports.

Enables LLM agents to access Global Database's company intelligence, including company profiles, financials, ownership, people search, prospecting, and KYB/compliance lookups against official registries.

Perfume database API with verified notes: 1,500+ perfumes, 160+ houses, 400+ raw materials in a fragrance ingredients database. 12 tools over MCP and REST, OpenAPI spec, free and keyless, answers in 10 languages. Look up a note or raw material and get the perfumes that use it, or a perfume and get its full top, heart and base pyramid. Built by Scento.

Read-only MCP server providing Wealthi's AI Coach with scoped access to student progress data from Firestore and Supabase, enabling AI to retrieve student profiles, progress, assessment results, and learning signals without direct database credentials.

Connect your database to your AI agent, read-only, without sharing your password. Maplith Bridge serves a folder of data files over MCP behind a token you create, and fills it from PostgreSQL under a role that can only read.

Enables MCP clients such as GitHub Copilot, Codex, Claude... to explore a SQL Server 2017+ database read-only: databases, schemas, tables, views, procedures, functions, indexes and dependency graphs, plus filtered, grouped, sampled and paginated queries capped by row limits.

Enables teams to capture and distill knowledge from sessions, meetings, and feeds into a searchable, vector-embedded graph, then retrieve or synthesize it conversationally via semantic search and citations.

MCP server to ask research questions about real-world datasets and get actual database records back, with auto-registration and trial credit.

Read-only MCP server that enables AI tools like Claude and Cursor to query the Avanti Fellows PostgreSQL database, providing schema inspection, data sampling, and SELECT query execution capabilities.

ClickHouse database integration with schema inspection and query capabilities

Analytical memory for AI agents: a real Postgres your agent connects to over MCP and queries in plain English — GROUP BY, JOIN, aggregate over what it remembered, not just top-k vector recall.

Unified MCP server for Arpe.io data tools enabling AI assistants to build, preview, and execute high-performance data commands including database export, transfer, pipeline, and migration.

Enables natural-language semantic search of a project's code through a local vector index, so questions that plain grep cannot match return ranked file:line references. It also indexes or refreshes projects on demand, reports index status, and optionally flags near-identical code across files.

Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your real database schema, it writes code that fails in production. LintBase acts as the bridge. It connects directly to your database, reads the ground truth of your live documents, and generates structured context optimized for AI. 🤖 Stops AI

An MCP server that integrates with Recraft AI to enable generation and manipulation of high-quality raster and vector images through tools like image generation, editing, vectorization, background removal, and upscaling.

Enables AI agents to build, edit, and publish live websites with hosting, database, auth, and domains via the Model Context Protocol.