"Information about OpenSearch" matching MCP servers:

Read-only MCP server for exploring and searching OpenSearch clusters, enabling log analysis, index exploration, and query execution.

MCP server for OpenSearch that enables AI assistants to interact with OpenSearch clusters through a standardized interface for search, index management, and cluster operations.

opensearch-mcp-server-py is a Model Context Protocol (MCP) server for OpenSearch that enables AI assistants to interact with OpenSearch clusters. It provides a standardized interface for AI models to perform operations like searching indices, retrieving mappings, and managing shards through both stdio and streaming (SSE/Streamable HTTP) protocols.

Enables interaction with OpenSearch clusters, providing tools to list indices, retrieve mappings, search using query DSL, and get shard information.

A Model Context Protocol server that enables querying and analyzing Wazuh security logs stored in OpenSearch, with features for searching alerts, getting detailed information, generating statistics, and visualizing trends.

Enables AI assistants to interact with OpenSearch clusters for searching indices, retrieving mappings, and managing shards through the MCP protocol.

Provides a semantic memory layer that integrates LLMs with OpenSearch, enabling storage and retrieval of memories within the OpenSearch engine.

A read-only MCP server that enables AI assistants to search, aggregate, and explore OpenSearch log data through 12 tools for connectivity, index discovery, search, and aggregations.

Context-efficient MCP server that executes OpenSearch DSL queries and returns synthesized output instead of raw JSON, reducing token usage by up to 90%.

A unified MCP server for multi-stand infrastructure testing, enabling REST API calls, PostgreSQL queries, and OpenSearch searches through a single config file.

An MCP Server implementation that integrates the Balldontlie API, to provide information about players, teams and games for the NBA, NFL and MLB.

Enables any MCP-compatible agent to query, diagnose, map, and operate Elasticsearch or OpenSearch clusters via REST, with read-only defaults and layered safety controls.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

Enables querying OpenTelemetry logs stored in OpenSearch across development and production environments. Provides tools for searching logs by various criteria including free-text Lucene queries, trace IDs, service names, error levels, and specific fields.

A read-only MCP server for investigating Amazon OpenSearch Service domains using natural language, with tools for cluster health, index management, search, and diagnostics, secured by allowed profiles and regions.

An MCP server that enables interaction with Elasticsearch and OpenSearch clusters for searching documents and managing indices. It provides tools for cluster health monitoring, index configuration, and general API requests.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

A Model Context Protocol server implementation that enables natural language interactions with OpenSearch clusters, allowing users to search documents, analyze indices, and manage clusters through simple conversational commands.

Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.

Enables AI agents to interact with INFINI Easysearch (compatible with Elasticsearch/OpenSearch APIs) through 121 tools covering cluster management, index operations, document manipulation, search queries, snapshots, and monitoring.