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"Querying Elasticsearch (ES)" matching MCP servers:

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    Enables querying Elasticsearch logs from AI assistants using natural language, with optional SSH tunnel support.
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    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).
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    MIT
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    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.
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    MIT
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    Enables AI assistants to search, analyze, and interact with Elasticsearch through natural language.
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    Apache 2.0
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    Facilitates interaction with Elasticsearch clusters by allowing users to perform index operations, document searches, and cluster management via a Model Context Protocol server and natural language commands.
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    Apache 2.0
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    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.
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    Apache 2.0
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    Connects to Elasticsearch clusters through the Model Context Protocol, enabling natural language querying and management of Elasticsearch data. Provides tools to search indices, list available indices, and retrieve index mappings.
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    Provides an MCP protocol interface for interacting with Elasticsearch 7.x databases, supporting comprehensive search functionality including aggregations, highlighting, and sorting.
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    Apache 2.0
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    MCP server for querying observability data from Elasticsearch, SkyWalking, and Prometheus/VictoriaMetrics, enabling AI models to search logs, traces, and metrics across environments.
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    MIT
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    Enables AI to automatically diagnose bugs by querying logs, tracing call chains, and analyzing code across multiple log platforms like Elasticsearch and Loki.
    MIT
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    Provides tools to query Elasticsearch indices, retrieve mappings, execute searches, and get cluster health stats.
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    MIT
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    MCP server that provides tools and resources to interact with Elasticsearch clusters, including listing indices, searching, and retrieving mappings.
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    MIT
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    Read-only MCP server for Elasticsearch log querying. Enables natural language search, filtering, context retrieval, and aggregation of logs.
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    A high-performance MCP server that connects tools like Cursor to Elasticsearch clusters using public-key authorization instead of API keys. It provides optimized tools for searching data, listing indices, and inspecting cluster mappings or shards with support for concurrent requests.
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    Connects LLMs to Elasticsearch with a Semantic-to-Lexical layer that translates technical field names into business knowledge, enabling autonomous querying without hardcoded domain logic.
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