MCP server connecting AI systems to Elasticsearch clusters
Overview
What is MCP Elasticsearch Server?
MCP Elasticsearch Server is a Model Context Protocol (MCP) server that connects AI systems to Elasticsearch clusters, enabling standardized querying capabilities.
How to use MCP Elasticsearch Server?
To use the server, clone the repository, build the project, and run it with the required Elasticsearch configuration. You can authenticate using either an API key or basic authentication.
Key features of MCP Elasticsearch Server?
- Multiple Authentication Methods: Supports API key and username/password authentication.
- Index Management: List indices with health status and document counts.
- Schema Discovery: Retrieve field mappings to understand index structure.
- Advanced Search: Execute complex Elasticsearch queries with aggregations and sorting.
- Structured Responses: JSON-formatted output with search metadata.
- Performance Monitoring: Query execution time tracking.
- Context Aware: Supports search execution with proper context cancellation.
Use cases of MCP Elasticsearch Server?
- Integrating AI assistants with Elasticsearch for enhanced data retrieval.
- Managing and querying large datasets efficiently.
- Monitoring and analyzing logs through advanced search capabilities.
FAQ from MCP Elasticsearch Server?
- What authentication methods are supported?
The server supports both API key and basic authentication methods.
- Can I manage Elasticsearch indices with this server?
Yes, you can list indices and retrieve their health status and document counts.
- Is there support for complex queries?
Yes, the server allows executing complex Elasticsearch queries with full DSL support.