Storm MCP Server with Sionic AI serverless RAG

Korean

Storm MCP(Model Context Protocol) Server

Storm MCP(Model Context Protocol) LLM LLM RAG RAG Anthropic Model Context Protocol Claude Desktop Storm Platform.

Sionic AI Storm Platform https://sionicstorm.ai API Token I want to know Yes.

Use

API Key는 scripts/run.sh 에 존재하는 export STORM_API_KEY='' 에 입력하세요.

Please select

• Sorry for the inconvenience.

• Message : Message (send_nonstream_chat, list_agents, list_buckets, upload_document_by_file).

• 파일 관리 : 파일 업로드, 읽기 및 관리를 위한 파일 시스템 작업을 구현합니다.

• API service : Storm API service.

Professional training

• main.py : MCP code.

• core/file_manager.py : FileSystemManager FileSystemManager .

• core/internal_api.py : Storm REST API.

• tools/tool_definitions.py : MCP settings.

• tools/tool_handlers.py : Handlers.

• tools/tool_upload_file.py : MCP download file.

Akitchan

MCP (LLM), (LLM), (LLM) Storm MCP Storm MCP LLM version.

How to start

Claude Desktop MCP

1. Open the setup file

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

2. JSON data MCP data:

{
  "mcpServers": {
    "storm": {
      "command": "sh",
      "args": [
        "/Users/sigridjineth/Desktop/work/storm-mcp-server/scripts/run.sh"
      ]
    }
  }
}

Related MCP server: MCP Python SDK

Japanese

Storm MCP(Model Context Protocol) Server

The Storm MCP (Model Context Protocol) Server is an open protocol that enables seamless integration between LLM applications and RAG data sources and tools. It implements Anthropic's Model Context Protocol and allows you to use the Storm Platform directly in Claude Desktop.

By integrating with Sionic AI's Storm Platform , you can connect and use your own powerful embedded models and vector DB products. Register per agent at https://sionicstorm.ai to get an API token and create your RAG solution in no time.

Usage Example

Please enter the API key in export STORM_API_KEY='' in scripts/run.sh .

Key Features

• Context sharing : Provides a standard protocol for interaction between LLM and data sources.

• Tool system : Provides a standardized way to define and invoke tools (send_nonstream_chat, list_agents, list_buckets, upload_document_by_file, etc.).

• File management : Implements file system operations for uploading, reading, and managing files.

• API Integration : Connect to Storm's API endpoints to provide a variety of features.

Project Structure

• main.py : Initializes the MCP server and sets up event handlers.

• core/file_manager.py : Implements the FileSystemManager class for file operations.

• core/internal_api.py : Contains API client functions for interacting with Storm's REST API endpoints.

• tools/tool_definitions.py : Defines the tools available on the MCP server.

• tools/tool_handlers.py : Implements handlers for tool operations.

• tools/tool_upload_file.py : Implements a separate file server for file operations with its own MCP handler.

architecture

MCP is designed with a three-layer structure between the host (LLM application), the client (protocol implementation), and the server (function provider). The Storm MCP server implements the server part and provides resources and tools to the LLM.

How to get started

To connect an MCP server in a Claude Desktop environment, the following settings must be applied:

1. Opening a configuration file

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

2. Add the MCP server settings in JSON:

{
  "mcpServers": {
    "storm": {
      "command": "sh",
      "args": [
        "/Users/sigridjineth/Desktop/work/storm-mcp-server/scripts/run.sh"
      ]
    }
  }
}