A Model Context Protocol (MCP) server with RAG (Retrieval-Augmented Generation) capabilities for intelligent document processing and question
If you want an AI assistant working directly with Chalee MCP Rag, the chalee mcp rag mcp server is the bridge. A Model Context Protocol (MCP) server with RAG (Retrieval-Augmented Generation) capabilities for intelligent document processing and question answering.
一个基于 Model Context Protocol (MCP) 的 **RAG（检索增强生成）**服务器，提供文档处理、向量存储和智能问答功能。
Once connected, the assistant can call these 5 tools directly:
macOS — 编辑 ~/Library/Application Support/Claude/claude_desktop_config.json:Windows — The Windows tool exposed by this serverinitialize_rag — The initialize_rag tool exposed by this serveradd_document — The add_document tool exposed by this serverask_question — interface AskQuestionResponse { question: string; answer: string; sources?: Array<{ content: string; similarity: number; metadata: Record<string, any>; }>The server is distributed via npm as COPY, so most clients can run it without a manual build step. Add it to your MCP client's configuration and restart the client to pick it up — the copy-paste configs for Claude Desktop, Claude Code and Cursor are on this page.
Before the server will start you need to supply one environment variable: OPENAI_API_KEY. Keep credentials in your client's env block or a secrets manager rather than committing them.
AI-service servers chain other models into your assistant, turning a single chat into a small production pipeline. Chalee MCP Rag sits in that group, and the shape of its toolset — macOS, Windows, initialize_rag among others — tells you what it is really for. Worth comparing against the other ai services servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.
| Tool | What it does |
|---|---|
| macOS | 编辑 ~/Library/Application Support/Claude/claude_desktop_config.json: |
| Windows | The Windows tool exposed by this server. |
| initialize_rag | The initialize_rag tool exposed by this server. |
| add_document | The add_document tool exposed by this server. |
| ask_question | interface AskQuestionResponse { question: string; answer: string; sources?: Array<{ content: string; similarity: number; metadata: Record<string, any>; }>; timestamp: string; } |
{
"mcpServers": {
"chalee-mcp-rag": {
"command": "npx",
"args": ["-y", "COPY"],
"env": {
"OPENAI_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.