Weaviate Vector Database
Unified vector database workflow for managing Weaviate objects, schemas, vector search via GraphQL, backups, and cluster operations. Used by AI engineers, platform operators, and data engineers to build and manage AI-powered applications.
What You Can Do
MCP Tools
check-weaviate-readiness
Check if the Weaviate instance is ready to accept requests
list-weaviate-objects
List objects stored in Weaviate, optionally filtered by collection class
create-weaviate-object
Create a new vector object in Weaviate with optional vector embedding
get-weaviate-object
Retrieve a specific Weaviate object by its UUID
delete-weaviate-object
Delete a Weaviate object by UUID
vector-search
Execute a GraphQL vector similarity search query against Weaviate
get-schema
Get the current data schema including all collection classes
create-collection-class
Create a new collection class in the Weaviate schema
batch-import-objects
Import multiple objects to Weaviate in a single batch operation
get-cluster-nodes
Get information about all nodes in the Weaviate cluster
create-backup
Create a backup of Weaviate data to a storage backend (s3, gcs, filesystem, azure)
list-backups
List available backups on a storage backend