Elasticsearch Vector MCP Server
Empower vector search via Elasticsearch — perform dense vector kNN searches, handle index mappings, and index embedding documents directly from any AI agent.
Vinkius AI Gateway prend en charge le streamable HTTP et le SSE.
Fonctionne avec tous les agents IA que vous utilisez déjà
…et tout client compatible MCP
Elasticsearch Vector MCP Server : voyez votre AI Agent en action
Capacités intégrées (6)
create_index
Create dense_vector index
delete_document
Delete a document
get_index
Get index info
index_document
Index a document
list_indexes
List all indexes
search
Dense vector knn search
Ce que ce connecteur débloque
Connect your Elasticsearch cluster to any AI agent and take full control of your vector search and semantic discovery workflows through natural conversation.
What you can do
- AI-Powered Vector Search — Perform raw K-Nearest Neighbors (kNN) computations mapping absolute semantic similarity across multi-dimensional embedding arrays
- Index Orchestration — Enumerate active storage namespaces and validate physical Elasticsearch clusters tracking explicit dimensional shards securely
- Schema Management — Analyze specific index mapping rules and provision strictly typed data structures enforcing numeric dimensions for cluster readiness
- Document Indexing — Command synchronous bulk insertions attaching exact
dense_vectorembedding payloads to persist data into raw Lucene partitions - Data Invalidation — Enforce immediate hard document vaporization finding specific exact UUIDs stripping records from physical indices seamlessly
- Metadata Auditing — Analyze dimensional constraints and matching similarity thresholds perfectly to verify your vector search configurations
How it works
1. Subscribe to this server
2. Enter your Elasticsearch Host URL and API Key (found in Kibana > Stack Management > Security > API Keys)
3. Start managing your vector search from Claude, Cursor, or any MCP-compatible client
Who is this for?
- AI Engineers — perform semantic searches and test embedding models without writing complex query DSL
- Software Developers — index embedding documents and verify kNN search results directly from the IDE or chat
- Data Scientists — monitor vector index mappings and verify dimensional constraints using natural language
- Ops Teams — verify cluster index health and manage vector storage namespaces in real-time
Questions fréquemment posées
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