Built by Metorial, the integration platform for agentic AI.
Provider Summary
search and query documents
manage indices and mappings
index and update documents
run aggregations and analytics
configure ingest pipelines
run ML inference tasks
monitor cluster health
manage snapshots and backups
manage users and roles
configure watcher alerts
Index, search, and analyze documents in Elasticsearch clusters. Create and manage indices with custom mappings and settings. Perform full-text search, structured queries, aggregations, and async search using Query DSL and ES|QL. Manage ingest pipelines to transform data before indexing. Run machine learning inference tasks including text embedding, reranking, completion, and anomaly detection. Monitor cluster health, node stats, and manage snapshots for backups. Configure cross-cluster replication and index lifecycle policies. Manage security including users, roles, API keys, and privileges. Explore graph relationships between terms. Set up Watcher alerts that poll data and trigger actions like emails or webhooks based on conditions.
Perform multiple index, create, update, or delete operations in a single API call. Much more efficient than individual requests when processing many documents.
Get the health status and key metrics of the Elasticsearch cluster including node count, shard allocation status, and pending tasks. Optionally include node-level statistics.
Remove a document from an Elasticsearch index by its ID. Returns the result of the deletion operation.
Execute an ES|QL query to filter, transform, and analyze data stored in Elasticsearch. ES|QL provides a pipe-based query language for powerful data exploration and manipulation.
Retrieve one or more documents by ID from an Elasticsearch index. Supports fetching a single document or multiple documents across indices using multi-get.
Discover relationships between terms in an Elasticsearch index. The graph explore API extracts and summarizes connections in your data, helping identify significant co-occurrences and related terms.
Create or replace a document in an Elasticsearch index. Provide JSON document content and optionally specify a document ID. If no ID is provided, Elasticsearch will auto-generate one. If an ID is provided and a document already exists with that ID, it will be replaced.
List all indices in the Elasticsearch cluster with their health status, document count, and storage size. Can also retrieve detailed information about a specific index including its mappings, settings, and aliases.
Create, delete, or list index aliases. Aliases provide alternative names for indices or groups of indices, enabling seamless index switching and multi-index queries.
Create, configure, open, close, or delete an Elasticsearch index. Supports setting mappings, settings, aliases, and number of replicas/shards during creation. Can also update mappings and settings on existing indices.
Create, update, delete, list, or simulate ingest pipelines. Pipelines consist of processors that transform and enrich documents before they are indexed. Use simulate to test a pipeline against sample documents.
Manage Elasticsearch security resources including users, roles, and API keys. Create, update, delete, and list users and roles for role-based access control. Create and invalidate API keys.
Create, restore, delete, or retrieve snapshots and snapshot repositories for cluster backups. Snapshots allow you to back up indices and cluster state for disaster recovery.
Create, update, delete, execute, activate, or deactivate Watcher alerts. Watches monitor data changes by running scheduled queries and triggering actions (email, webhook, index, logging) when conditions are met.
Copy documents from one index to another, optionally applying a query filter or transformations via a script. Useful for migrating data between indices, changing mappings, or applying pipeline processing to existing data.
Execute a machine learning inference task using a configured inference endpoint. Supports text embedding, sparse embedding, reranking, completion, and chat completion tasks. Can also list or manage inference endpoints.
Search and query documents in Elasticsearch using the full Query DSL. Supports full-text search, term-level queries, compound queries, aggregations, sorting, pagination, and source filtering. Can target a specific index or search across all indices.
Partially update an existing document in an Elasticsearch index. Supports partial document updates (merge fields) or script-based updates for more complex modifications. Unlike indexing, this only modifies specified fields without replacing the entire document.
This integration is licensed under the AGPL-3.0 License.
Built with ❤️ by Metorial