Databases

An MCP server that gives an AI assistant tools to search documents, manage indices, aliases and data streams, and inspect cluster health in Elasticsearch or OpenSearch.

• MCP servers
• Databases

A Swift vector database for on-device apps, combining local vector storage and hybrid search with pluggable embedding providers, including Apple's MLX and NaturalLanguage frameworks.

• Databases

A graph and vector database built on Neo4j that accepts any JSON and returns typed, searchable, relationship-aware records without a schema or migrations, meant as a memory layer for AI agents.

• Agent memory
• Databases

Hibernate Tools is a set of tools that reverse-engineers Hibernate and JPA mapping artifacts from an existing database, and wraps that functionality as Ant tasks and Maven plugins for build integration.

• Databases

A managed retrieval-augmented-generation API server, built with FastAPI and LangChain, that exposes collections and documents over REST with PostgreSQL and pgvector for storage and vector search.

• RAG
• Databases

An MCP server exposing read-only Apache Doris capabilities to AI agents, organized as eight stable domains with fifty-five progressively disclosed child tools covering catalog, query, cluster, ingestion, search, governance and lakehouse operations.

• MCP servers
• Databases

A curated list of vector database services, libraries, benchmarks, and papers, covering high-dimensional structure and vector search and comparing options across the space.

• Databases
• Curated lists

A persistent, embedded graph database for Python that stores data as a triple store and is queried through a chainable Python query language called Torque, with no server to run.

• Databases

Qdrant web-ui is a self-hosted web interface for viewing and managing collections in the Qdrant vector search engine, comparable to Kibana for Elasticsearch, with no additional services required.

• Databases

Antfly is a search-and-inference database written in Zig that combines full-text, dense, sparse and late-interaction vector search with graph traversal in one engine, running the models that chunk, embed, rerank and extract data inside the process.

• RAG
• Databases

The production Python client for building AI applications on Redis, covering vector index management, hybrid vector and full-text search, semantic caching, and an MCP server for exposing Redis indexes to AI clients.

• RAG
• Databases

The official Python client for the Pinecone vector database, used to create and manage indexes, upsert and query records, and run inference operations.

• Databases

The JavaScript and TypeScript SDK for the Qdrant vector search engine, published as a main package plus separate lightweight REST and gRPC clients.

• Databases

A single Rust binary that plans, applies and rolls back changes to a production ontology, reports every consequence of a change before it is applied, and produces a Lean 4 proof of the result that a reviewer can re-check without trusting the tool.

• Databases

A sample chat application and FastAPI backend that answers questions about rows in a PostgreSQL table using OpenAI chat models, hybrid vector and full-text search, and function calling to turn natural-language filters into SQL conditions.

• RAG
• Databases

An MCP server that connects AI assistants and IDEs to DuckDB's SQL engine, letting them query local DuckDB files, in-memory databases, S3-hosted databases and MotherDuck, browse catalogs, and switch connections at runtime.

• MCP servers
• Databases

A language-model search engine built as a reboot of an older project, combining a vector-space search engine, a vector database, and a general-purpose key-value store.

• Databases

Neon MCP Server is an open-source MCP server that lets an AI agent manage Neon Postgres databases in natural language, creating projects and branches, running queries and performing migrations.

• MCP servers
• Databases

A local, file-backed vector database for Node.js with an optional gRPC server for cross-language access, aimed at applications that want a Pinecone-like index stored on disk.

• Databases

Moss is a semantic search runtime that embeds directly in an application, built for conversational AI agents that need retrieval latency under 10 milliseconds without running a separate vector database.

• RAG
• Databases

The Elasticsearch MCP Server connects AI agents to Elasticsearch through the Model Context Protocol, letting them query, analyze and retrieve data in natural language without custom APIs. It is deprecated and superseded by the Elastic Agent Builder MCP endpoint.

• MCP servers
• Databases

A Visual Studio extension and command-line tool that reverse-engineers an existing database into Entity Framework Code First POCO classes, configuration mappings, a DbContext, and a fake DbContext for unit testing.

• Databases

NucliaDB is a hybrid search database for unstructured data, combining vector, full-text and graph indexes with support for large datasets and multi-tenancy.

• Databases

A simple vector database implemented in plain numpy, with no server or configuration to set up, that stores embeddings in a single portable context file.

• Databases