OpenSearch MCP Server: Lightning-Fast Search & Analytics

Dominate search & analytics with OpenSearch MCP Server – enterprise-grade, lightning-fast, and built for your toughest data challenges.

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About OpenSearch MCP Server

What is OpenSearch MCP Server: Lightning-Fast Search & Analytics?

OpenSearch MCP Server is a powerful tool that bridges your applications to OpenSearch clusters using the Machine Coding Protocol (MCP). It’s designed to handle complex search and analytics tasks with blazing speed, making it ideal for developers and data teams. Think of it as a supercharged middleman that simplifies managing indices, monitoring clusters, and crunching document data—all while keeping your workflows smooth.

How to Use OpenSearch MCP Server: Lightning-Fast Search & Analytics?

Getting started is straightforward:

Install the server: Clone the repo, set up a virtual environment, and run `uv pip install -e .`.
Configure: Update the `.env` file with your OpenSearch credentials and host details.
Fire it up: Launch the server with `uv run` and specify the port. Boom—you’re live.
Integrate: Plug the server URL into your app’s config file to start leveraging its features.

Need to test it out? Run the included unit tests to ensure everything’s ticking.

OpenSearch MCP Server Features

Key Features of OpenSearch MCP Server: Lightning-Fast Search & Analytics?

This server packs a punch with three core toolsets:

Index Mastery: List all indices, inspect mappings, and tweak settings with ease. Perfect for keeping your data structure tidy.
Cluster Oversight: Get real-time health checks and stats to monitor performance without breaking a sweat.
Document Power: Perform lightning-fast searches across your datasets—no more waiting around for results.

Use Cases of OpenSearch MCP Server: Lightning-Fast Search & Analytics?

Here’s where it shines:

Data Analysts: Track cluster performance in real time to optimize resource usage.
App Developers: Embed seamless search functionality into desktop apps with minimal coding.
Enterprise Teams: Manage large-scale indices and run instant analytics for reporting or dashboards.
DevOps: Automate index management tasks to keep operations running like a well-oiled machine.

OpenSearch MCP Server FAQ

FAQ from OpenSearch MCP Server: Lightning-Fast Search & Analytics?

Q: Is this compatible with all OpenSearch versions?
A: Works best with versions 2.x+. Check the docs for specific compatibility notes.

Q: Can it handle high-traffic search requests?
A: Built for speed, it’s optimized for heavy workloads—just make sure your OpenSearch cluster is scaled appropriately.

Q: What if I get an authentication error?
A: Double-check your `.env` file credentials and ensure the server can reach your OpenSearch host.

Q: Can I customize the MCP endpoints?
A: Absolutely—dig into the source code or open an issue on GitHub for custom feature requests.

Content

OpenSearch MCP Server

MCP (Machine Coding Protocol) server for OpenSearch integration.

Features

Index Management Tools:
- List all indices in OpenSearch cluster
- Get index mapping
- Get index settings
Cluster Management Tools:
- Get cluster health status
- Get cluster statistics
Document Tools:
- Search documents

Installation

# Clone the repository
git clone https://github.com/your-username/opensearch-mcp-server.git
cd opensearch-mcp-server

# Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install the package
pip install uv
uv pip install -e .

Configuration

Create a .env file in the root directory with the following variables:

OPENSEARCH_HOST=https://localhost:9200
OPENSEARCH_USERNAME=xxxx
OPENSEARCH_PASSWORD=xxxx

Adjust the values to match your OpenSearch configuration.

Usage

Run the MCP server:

uv run opensearch-mcp-server --transport=sse --port=<port>

Usage with Desktop App

To integrate this server with a desktop app, add the following to your app's server configuration:

{
  "mcpServers": {
    "opensearch": {
      "url": "http://<host>:<port>>/sse"
    }
  }
}

Development

# Install dependencies
uv pip install -e .

# Run tests
uv run pytest -vv -s test_opensearch.py

License

MIT

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