OpenSearch
About
Integrates with OpenSearch to enable powerful full-text search, data aggregation, and real-time analytics capabilities for applications requiring advanced search and log analysis.
Details
- Author
- ibrookssdx
- Repository
- ibrooksSDX/mcp-server-opensearch
- GitHub stars
- 4
- Downloads
- 304
- License
- Apache License 2.0
- Categories
- AI, Design, Developer Tools, Search, Security, Infrastructure, Frontend, Database
Jump to
- Provides a single tool search-openSearch to query OpenSearch.
- Acts as a semantic memory layer on top of OpenSearch.
- Supports configuration via CLI arguments or environment variables.
- Can be installed automatically via Smithery for Claude Desktop.
- Uses FastMCP for development and testing.
- Includes a demo script (demo.py) for quick setup.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
OpenSearchCommand (node, npx, python, etc.)uvxArguments-
Argument 1
mcp-server-opensearch -
Argument 2
--opensearch-url -
Argument 3
http://localhost:9200 -
Argument 4
--opensearch-api-key -
Argument 5
your_api_key -
Argument 6
--index-name -
Argument 7
your_index_name
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
```shell
pip install opensearch-py[async]
search-openSearch
Store a memory in the OpenSearch database. Input: query (json): prepared json query message. Returns: Confirmation message.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"opensearch": {
"cwd": "string",
"env": {},
"args": [
"mcp-server-opensearch",
"--opensearch-url",
"http://localhost:9200",
"--opensearch-api-key",
"your_api_key",
"--index-name",
"your_index_name"
],
"shell": false,
"command": "uvx"
}
}
}Linux
{
"cwd": "string",
"env": [],
"args": [
"mcp-server-opensearch",
"--opensearch-url",
"http://localhost:9200",
"--opensearch-api-key",
"your_api_key",
"--index-name",
"your_index_name"
],
"shell": false,
"command": "uvx"
}Macos
{
"cwd": "string",
"env": [],
"args": [
"mcp-server-opensearch",
"--opensearch-url",
"http://localhost:9200",
"--opensearch-api-key",
"your_api_key",
"--index-name",
"your_index_name"
],
"shell": false,
"command": "uvx"
}Windows
{
"cwd": "string",
"env": [],
"args": [
"mcp-server-opensearch",
"--opensearch-url",
"http://localhost:9200",
"--opensearch-api-key",
"your_api_key",
"--index-name",
"your_index_name"
],
"shell": false,
"command": "uvx"
}mcp-server-opensearch: An OpenSearch MCP Server
> The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
This repository is an example of how to create a MCP server for OpenSearch, a distributed search and analytics engine.
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