Ragie Model Context Protocol Server

Name: Ragie Model Context Protocol Server
Author: ragieai

@ragieai

Repository

About Ragie Model Context Protocol Server

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

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Overview

What is Ragie Model Context Protocol Server?

The Ragie Model Context Protocol Server is an MCP server that provides AI models with access to Ragie’s knowledge base retrieval capabilities via a single “retrieve” tool. It is intended for developers integrating Ragie-powered knowledge retrieval into AI applications that support MCP.

How to use Ragie Model Context Protocol Server?

Install and run with npx using your Ragie API key: RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server. Optionally, pass --description or --partition flags. Configure it in Cursor via an mcp.json file or a shell script, or in Claude Desktop via claude_desktop_config.json. The server listens on stdio for MCP protocol messages.

Key features of Ragie Model Context Protocol Server

Provides a single “retrieve” tool for knowledge base queries.
Accepts query, topK, rerank, and recencyBias parameters.
Returns an array of relevant content chunks.
Supports custom tool description and partition ID overrides.
Runs on Node.js >= 18 with a Ragie API key.
Works with Cursor and Claude Desktop MCP configurations.

Use cases of Ragie Model Context Protocol Server

Enable Claude Desktop to search a company knowledge base.
Let Cursor AI retrieve information from Ragie during development.
Integrate Ragie retrieval into any MCP-supporting AI assistant.
Query partitioned knowledge bases with the --partition option.

FAQ from Ragie Model Context Protocol Server

What does the “retrieve” tool do?

It searches the Ragie knowledge base for information matching a provided query and returns an array of text chunks, with optional reranking and recency bias.

What are the runtime requirements?

Node.js 18 or later and a valid Ragie API key (set as the RAGIE_API_KEY environment variable).

How do I configure it for Claude Desktop?

Create or edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/…, Windows: %APPDATA%/Claude/…) with the npx command, API key, and optional partition ID, then restart Claude.