Opensearch MCP Server Py

• OpenSearch MCP Server
• Installing opensearch-mcp-server-py
• Available tools
• User Guide
• Agent Memory
• Contributing
• Code of Conduct
• License
• Copyright

OpenSearch MCP Server

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.

Key features:

• Seamless integration with AI assistants and LLMs through the MCP protocol
• Support for both stdio and streaming server transports (SSE and Streamable HTTP)
• Built-in tools for common OpenSearch operations
• Dynamic per-call connection parameters for targeting different clusters without server reconfiguration
• Easy integration with Claude Desktop and LangChain
• Secure authentication using basic auth, IAM roles, header-based auth, and OpenSearch mTLS

For detailed setup, including Kubernetes deployment and mTLS configuration, see the User Guide.

Installing opensearch-mcp-server-py

Opensearch-mcp-server-py can be installed from PyPI via pip:

pip install opensearch-mcp-server-py

Zero-Config Setup

The server can be started with no environment variables at all. Agents provide connection details dynamically on each tool call:

{
  "mcpServers": {
    "opensearch": {
      "command": "uvx",
      "args": ["opensearch-mcp-server-py"]
    }
  }
}

With this setup, agents pass opensearch_url and authentication parameters directly when calling any tool. This is useful when agents discover endpoints from a knowledge base, runbook, or SOP, or when a single agent needs to work with multiple clusters in one session. See Dynamic Connection Parameters for details.

Available Tools

By default, only core tools are enabled to provide essential OpenSearch functionality:

Core Tools (Enabled by Default)

Core tools are grouped under the core_tools category and can be disabled at once using OPENSEARCH_DISABLED_CATEGORIES=core_tools. Avoid creating custom categories with this name as they will override the built-in category.

• ListIndexTool: Lists all indices in OpenSearch with full information including docs.count, docs.deleted, store.size, etc. If an index parameter is provided, returns detailed information about that specific index.
• IndexMappingTool: Retrieves index mapping and setting information for an index in OpenSearch.
• SearchIndexTool: Searches an index using a query written in query domain-specific language (DSL) in OpenSearch.
• GetShardsTool: Gets information about shards

... View full README on GitHub