Milvus (Open-Source Vector Database) MCP Server
Manage vector storage via Milvus — perform ANN searches, query scalar entities, and audit collections.
Vinkius AI Gateway soporta streamable HTTP y SSE.
Funciona con todos los agentes de IA que ya usas
…y cualquier cliente compatible con MCP
Milvus MCP Server: mira tu AI Agent en acción
Capacidades integradas (7)
delete_entities
Irreversibly delete specific vector records utilizing primary keys
describe_collection
Explore the explicit schema mapping and indexing definition of a Milvus collection
get_collection_stats
Get collection statistics bounding row counts natively
get_entities
Extract unique vector items bounding exactly by known Primary Keys
list_collections
Always query this first. List index collections tracked inside the Milvus Vector Database
query_entities
Query explicitly using scalar expressions to retrieve entities
search_vectors
Make sure to feed a strict explicit JSON Array matching exact dimensions. Search nearest vector neighbors matching implicit embedding inputs
Lo que este conector desbloquea
Connect your Milvus instance to any AI agent and take full control of your high-performance vector search, embedding storage, and scalar data management through natural conversation.
What you can do
- Vector Search Orchestration — Execute Approximate Nearest Neighbor (ANN) searches against your collections by providing raw embedding vectors to retrieve semantically relevant matches directly from your agent
- Scalar Query Filters — Use sophisticated scalar expressions to filter entities by structured fields (e.g., tags, IDs, dates) alongside your vector search for precise data retrieval
- Collection Lifecycle Audit — List all managed vector collections and retrieve detailed schema definitions, including dimensions, primary keys, and index types natively
- Performance Statistics — Extract real-time metrics for your collections, including entity counts and physical memory usage, to monitor the health of your vector store
- Precision Retrieval — Fetch specific vector items by their primary keys, bypassing standard semantic boundaries to audit exact data points securely
- Data Management — Irreversibly delete specific vector records using primary identifiers to maintain a clean and optimized search index across your Milvus instance
How it works
1. Subscribe to this server
2. Enter your Milvus Base URL and API Key (or Zilliz Cloud Token)
3. Start optimizing your vector search from Claude, Cursor, or any MCP-compatible client
Who is this for?
- ML Engineers — test vector relevance and verify embedding dimensions through natural conversation without manual SDK scripts
- Search Architects — audit collection schemas and monitor indexing performance directly from your workspace
- Software Developers — integrate AI-powered retrieval into applications and manage vector lifecycles across multiple Milvus environments efficiently
Preguntas frecuentes
Dale a tus agentes de IA el poder de Milvus
Accede a Milvus y a más de 2.000 servidores MCP — listos para que tus agentes los usen, ahora mismo. Sin código pegamento. Sin integraciones personalizadas. Solo conecta el Vinkius AI Gateway y deja que tus agentes trabajen.
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