Allows LangChain agents to use OpenSearch MCP tools via SSE transport.
Provides tools to list indices, retrieve index mappings, search using DSL, and get shard information.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@opensearch-mcp-server list all indices"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A minimal Model Context Protocol (MCP) server for OpenSearch exposing 4 tools over stdio and sse server.
ListIndexTool: Lists all indices in OpenSearch.
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 in OpenSearch.
More tools coming soon. Click here
Related MCP server: Elastic MCP Server
Install from PyPI:
pip install test-opensearch-mcpBasic Authentication
export OPENSEARCH_URL="<your_opensearch_domain_url>"
export OPENSEARCH_USERNAME="<your_opensearch_domain_username>"
export OPENSEARCH_PASSWORD="<your_opensearch_domain_password>"IAM Role Authentication
export OPENSEARCH_URL="<your_opensearch_domain_url>"
export AWS_REGION="<your_aws_region>"
export AWS_ACCESS_KEY="<your_aws_access_key>"
export AWS_SECRET_ACCESS_KEY="<your_aws_secret_access_key>"
export AWS_SESSION_TOKEN="<your_aws_session_token>"# Stdio Server
python -m mcp_server_opensearch
# SSE Server
python -m mcp_server_opensearch --transport sseUsing the Published PyPI Package (Recommended)
{
"mcpServers": {
"opensearch-mcp-server": {
"command": "uvx",
"args": [
"test-opensearch-mcp"
],
"env": {
// Required
"OPENSEARCH_URL": "<your_opensearch_domain_url>",
// For Basic Authentication
"OPENSEARCH_USERNAME": "<your_opensearch_domain_username>",
"OPENSEARCH_PASSWORD": "<your_opensearch_domain_password>",
// For IAM Role Authentication
"AWS_REGION": "<your_aws_region>",
"AWS_ACCESS_KEY": "<your_aws_access_key>",
"AWS_SECRET_ACCESS_KEY": "<your_aws_secret_access_key>",
"AWS_SESSION_TOKEN": "<your_aws_session_token>"
}
}
}
}Using the Installed Package (via pip):
{
"mcpServers": {
"opensearch-mcp-server": {
"command": "python", // Or full path to python with PyPI package installed
"args": [
"-m",
"mcp_server_opensearch"
],
"env": {
// Required
"OPENSEARCH_URL": "<your_opensearch_domain_url>",
// For Basic Authentication
"OPENSEARCH_USERNAME": "<your_opensearch_domain_username>",
"OPENSEARCH_PASSWORD": "<your_opensearch_domain_password>",
// For IAM Role Authentication
"AWS_REGION": "<your_aws_region>",
"AWS_ACCESS_KEY": "<your_aws_access_key>",
"AWS_SECRET_ACCESS_KEY": "<your_aws_secret_access_key>",
"AWS_SESSION_TOKEN": "<your_aws_session_token>"
}
}
}
}The OpenSearch MCP server can be easily integrated with LangChain using the SSE server transport
Install required packages
pip install langchain langchain-mcp-adapters langchain-openaiSet up OpenAI API key
export OPENAI_API_KEY="<your-openai-key>"Ensure OpenSearch MCP server is running in SSE mode
python -m mcp_server_opensearch --transport sseimport asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langchain.agents import AgentType, initialize_agent
# Initialize LLM (can use any LangChain-compatible LLM)
model = ChatOpenAI(model="gpt-4o")
async def main():
# Connect to MCP server and create agent
async with MultiServerMCPClient({
"opensearch-mcp-server": {
"transport": "sse",
"url": "http://localhost:9900/sse", # SSE server endpoint
"headers": {
"Authorization": "Bearer secret-token",
}
}
}) as client:
tools = client.get_tools()
agent = initialize_agent(
tools=tools,
llm=model,
agent=AgentType.OPENAI_FUNCTIONS,
verbose=True, # Enables detailed output of the agent's thought process
)
# Example query
await agent.ainvoke({"input": "List all indices"})
if __name__ == "__main__":
asyncio.run(main())Notes:
The script is compatible with any LLM that integrates with LangChain and supports tool calling
Make sure the OpenSearch MCP server is running before executing the script
Configure authentication and environment variables as needed
Interested in contributing? Check out our:
Development Guide - Setup your development environment
Contributing Guidelines - Learn how to contribute
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Search your Obsidian vault to quickly find notes by title or keyword, summarize related content, a…
Gateway between LLM agents and world data through eight tools and a bundled endpoint catalog.
Search and fetch Wikidata entities, execute SPARQL queries, and resolve external identifiers.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/rithinpullela/opensearch-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server