"Analyzing data in OpenSearch" matching MCP servers:

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.

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.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

Read-only MCP server for querying ClickHouse (product telemetry) and Elasticsearch (download analytics), built for Percona VISTA.

MCP server providing AI assistants access to Polish public registries (KRS, CEIDG) and statistical data (GUS BDL) for querying companies, sole proprietorships, and regional statistics.

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

An MCP server for internal data platforms that enables search, viewing, tracing, and read-only querying of business assets like dashboards, metrics, and events.

Connect any AI to PostgreSQL, MySQL, or SQL Server — 24 dialect-aware tools for query, schema, optimization, and more.

Provides tools for interacting with SQL Server databases, enabling users to retrieve paginated table data, inspect schemas, and count records. It features enforced pagination and secure configuration options to manage database operations efficiently through natural language.

An MCP server for interacting with SQL Server databases that enables schema inspection, record counting, and paginated data retrieval. It provides tools to explore table structures and fetch specific records while enforcing safety limits on data volume.

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.