该项目已不再需要。Ragie 现在原生支持 MCP，作为可流式 HTTP 服务器。文档请见此处：[[https://docs.ragie.ai/docs/mcp-overview]

如果你希望公司内的用户能够访问你在Claude或ChatGPT等应用中的知识库，可能需要MCP Bridge。

Ragie 模型上下文协议服务器

一个模型上下文协议（MCP）服务器，提供访问Ragie知识库检索能力。

描述

该服务器实现了模型上下文协议，使 AI 模型能够从 Ragie 知识库中检索信息。它提供了一个名为“检索”的单一工具，允许查询知识库中相关信息。

先修条件

• Node.js >= 18
• Ragie API 密钥

安装

服务器需要以下环境变量：

• RAGIE_API_KEY（必需）：您的Ragie API认证密钥

服务器会启动并监听 MCP 协议消息。

用npx安装并运行服务器：

命令行选项

服务器支持以下命令行选项：

• --description, -d ：用自定义文本覆盖默认工具描述

IMPORTANT!

This project is no longer needed. Ragie now supports MCP natively as a streamable HTTP server. See docs here: [https://docs.ragie.ai/docs/mcp-overview]

If you would like users within your company to be able to access you knowledge base in applications like Claude or ChatGPT, you may need MCP Bridge

Ragie Model Context Protocol Server

A Model Context Protocol (MCP) server that provides access to Ragie’s knowledge base retrieval capabilities.

Description

This server implements the Model Context Protocol to enable AI models to retrieve information from a Ragie knowledge base. It provides a single tool called “retrieve” that allows querying the knowledge base for relevant information.

Prerequisites

• Node.js >= 18
• A Ragie API key

Installation

The server requires the following environment variable:

• RAGIE_API_KEY (required): Your Ragie API authentication key

The server will start and listen on stdio for MCP protocol messages.

Install and run the server with npx:

RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server

Command Line Options

The server supports the following command line options:

• --description, -d : Override the default tool description with custom text
• --partition, -p : Specify the Ragie partition ID to query

Examples:

# With custom description
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server --description "Search the company knowledge base for information"

# With partition specified
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server --partition your_partition_id

# Using both options
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server --description "Search the company knowledge base" --partition your_partition_id

Cursor Configuration

To use this MCP server with Cursor:

Option 1: Create an MCP configuration file

1. Save a file called mcp.json

• For tools specific to a project, create a .cursor/mcp.json file in your project directory. This allows you to define MCP servers that are only available within that specific project.
• For tools that you want to use across all projects, create a ~/.cursor/mcp.json file in your home directory. This makes MCP servers available in all your Cursor workspaces.

Example mcp.json:

{
  "mcpServers": {
    "ragie": {
      "command": "npx",
      "args": [
        "-y",
        "@ragieai/mcp-server",
        "--partition",
        "optional_partition_id"
      ],
      "env": {
        "RAGIE_API_KEY": "your_api_key"
      }
    }
  }
}

Option 2: Use a shell script

1. Save a file called ragie-mcp.sh on your system:

#!/usr/bin/env bash

export RAGIE_API_KEY="your_api_key"

npx -y @ragieai/mcp-server --partition optional_partition_id

2. Give the file execute permissions: chmod +x ragie-mcp.sh