Elasticsearch MCP Server is a Model Context Protocol (MCP) server implementation that provides interaction with Elasticsearch. It enables users to search documents, analyze indices, and manage clusters through a set of tools.
The Elasticsearch MCP Server simplifies interactions with Elasticsearch by offering features such as index operations (list indices, retrieve mappings), document operations (search using Query DSL), and cluster operations (health status, statistical information). It can be integrated into applications like Claude Desktop for natural language-based Elasticsearch queries.
Developers, data engineers, and DevOps professionals who work with Elasticsearch clusters can benefit from this tool. It is especially useful for those looking to streamline Elasticsearch operations via natural language commands in platforms like Claude Desktop.
You can run the Elasticsearch MCP Server locally or in a Docker environment. For local development, it can be installed via Smithery, uvx, or uv. It integrates well with Claude Desktop, where configurations can be adjusted based on the operating system (macOS or Windows).
The initial release of Elasticsearch MCP Server (v1.0.0) occurred prior to January 18, 2025, as indicated by the timestamp provided.
You can start a 3-node Elasticsearch cluster along with Kibana using Docker Compose by running the command: `docker-compose up -d`. The default Elasticsearch username is 'elastic' and the password is 'test123'. Access Kibana at http://localhost:5601.
There are three main methods: (1) Install automatically via Smithery using `npx -y @smithery/cli install elasticsearch-mcp-server --client claude`, (2) Use `uvx` to install directly from PyPI, or (3) Use `uv` with a locally cloned repository. Each method requires adding specific configurations to the `claude_desktop_config.json` file.
You can perform Index Operations (e.g., list indices, get mappings/settings), Document Operations (e.g., search documents using Query DSL), and Cluster Operations (e.g., check cluster health/stats).
Yes, Elasticsearch MCP Server is licensed under the Apache License Version 2.0, making it open-source software.
Yes, when integrated with Claude Desktop, Elasticsearch MCP Server allows users to issue natural language commands like 'List all indices in the cluster' or 'Show me the cluster health status.'
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
At mcpserver.shop, you can browse our MCP Server Directory. The directory is categorized by industry (e.g., finance, healthcare, education), and each server comes with detailed descriptions and tags to help you quickly find the option that suits your needs.
The MCP Server Directory on mcpserver.shop is free to browse. However, some servers are hosted by third-party providers and may involve usage fees. Check the detailed page of each server for specific information.
MCP Servers support a wide range of data sources, including databases, APIs, cloud services, and custom tools. The flexibility of the MCP protocol allows it to connect almost any type of data source to AI models.
MCP Servers are primarily designed for developers, data scientists, and AI app builders. However, mcpserver.shop provides detailed documentation and guides to help users of varying technical levels get started easily.
Yes, MCP is an open-source protocol that encourages community participation and collaboration. For more details or to contribute, visit the official MCP documentation.
On mcpserver.shop, each MCP Server’s detailed page includes the provider’s contact information or a link. You can directly reach out to the provider for more details or technical support.