Empower vector search via Elasticsearch — perform dense vector kNN searches, handle index mappings, and index embedding documents directly from any AI agent.

Power your RAG and search via Jina AI — generate embeddings, rerank documents, read URLs, and perform semantic web search.

Manage AI inference via Mistral — execute chat completions, generate RAG embeddings, and audit frontier models.

Manage vector storage via MongoDB Atlas — perform similarity searches, query MQL documents, and audit collections.

Access LLMs, embeddings, code generation, and reasoning via NVIDIA API Catalog.

Run k-NN vector searches on OpenSearch — create indexes, upsert embeddings, query similar documents, and manage your vector store from any AI agent.

Run vector similarity searches, manage embedding tables, and build AI-powered retrieval pipelines — all directly inside your existing PostgreSQL database.

Manage vector embeddings via Chroma — list collections, query embeddings, and audit document counts directly from any AI agent.

Manage vector search and NoSQL via Couchbase — execute N1QL queries, perform KNN vector searches, and audit documents directly from any AI agent.

Empower LLM applications via Fireworks AI — perform ultra-fast chat completions, generate embeddings and images, and transcribe audio directly from any AI agent.

Manage vectorized data via LanceDB — perform similarity searches, create tables, and manage multi-modal embeddings.

Connect your AI to Supabase Vector. Execute pgvector semantic searches, manage embeddings, and run relational database queries directly from your terminal.

Bring Google's massive vector matching power to your AI agent. Search billions of semantic embeddings and administer Vertex Index endpoints directly in chat.

Equip your AI to autonomously manage embeddings, run KNN similarity searches, and administrate vector indexes natively inside your Redis stack.

Manage vector storage via Milvus — perform ANN searches, query scalar entities, and audit collections.

Power your agent with Vald — query, insert, and manage dense vectors on a highly scalable, distributed nearest-neighbor engine.