Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"opensearch-mcp-server-py": {
"args": [
"opensearch-mcp-server-py"
],
"command": "uvx"
}
}
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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:
For detailed setup, including Kubernetes deployment and mTLS configuration, see the User Guide.
Opensearch-mcp-server-py can be installed from PyPI via pip:
pip install opensearch-mcp-server-py
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.
By default, only core tools are enabled to provide essential OpenSearch functionality:
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.