Elasticsearch is a distributed, free and open search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured.
Provides Elasticsearch integration for storing and searching extracted financial report data, including bulk indexing of records, BM25 search with highlight snippets, and index deletion.
An MCP server for Chinese financial reports, providing 44 tools to resolve companies, list/retrieve filings, extract report sections, run AI-based indicator extraction, search via Elasticsearch, and browse a 21,698-rule industry rules dashboard.
44
MIT
Why this server?
Analyzes Elasticsearch integration in a Symfony project, including indexes, queries, and client configuration.
Enables AI assistants to perform read-only introspection of Symfony applications, exposing routes, controllers, services, entities, database schema, migrations, logs, and more via MCP tools.
10
5
50 npm
MIT
Why this server?
Provides documentation and code validation for XanoScript, including integration guidance for Elasticsearch search operations.
An MCP server and standalone library that gives AI assistants superpowers for developing on Xano — complete with documentation, code validation, and workflow guides.
7
595 npm
9
MIT
Why this server?
Provides access to Elasticsearch indices, allowing users to list indices, inspect field mappings, and execute search queries using full Query DSL capabilities with automatic highlighting.
Connects Claude and other MCP clients to Elasticsearch data, allowing users to interact with their Elasticsearch indices through natural language conversations.
3
1,690 npm
718
Apache 2.0
Why this server?
Allows querying and managing Elasticsearch indices and data within WhoDB.
MCP server that stream-parses NDJSON log files without loading them into memory — filter by pattern, detect error spikes via Z-score analysis, summarize severity timelines by time window.
8
24 npm
MIT
Why this server?
Allows searching and analyzing Elasticsearch logs in ECS format, providing tools for error search, pattern detection, trend analysis, trace context, and error comparison.
Enables LLM agents to search and analyze Elasticsearch logs for errors, detect recurring patterns, analyze error-rate trends, and retrieve full trace context through MCP tools.
6
MIT
Why this server?
Provides tools for cluster health checks, index management, search with Query DSL, document retrieval, and bulk indexing operations.
A universal MCP server enabling AI assistants to query and manage six database engines (Postgres, Redis, Elasticsearch, MySQL, MongoDB, LDAP) through 113+ tools with read-only safety and fault tolerance.
100
17 npm
82
MIT
Why this server?
Provides direct Elasticsearch access for log queries, aggregations, and index discovery, with optional Kibana Console proxy fallback.
MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, and dashboard browsing. Hits Elasticsearch REST API directly for log queries; falls back to Kibana
Console proxy when no direct ES URL is configured. Supports ApiKey auth (best for agents), Basic auth, and anonymous access. All 5 tools are read-only (readOnlyHint: true). Returns
structured JSON (outputSchema).
