Ragie Model Context Protocol Server

Name: Ragie Model Context Protocol Server
Author: andyciggy

@andyciggy

Repository

About Ragie Model Context Protocol Server

No overview available yet

#ragie-mcp #model-context-protocol #knowledge-retrieval

Basic information

Config

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

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Ragie Model Context Protocol Server?

The Ragie Model Context Protocol Server implements the Model Context Protocol (MCP) 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. It is built for developers and AI assistants that need to integrate Ragie’s knowledge retrieval capabilities.

How to use Ragie Model Context Protocol Server?

Install and run with npx, setting the required RAGIE_API_KEY environment variable. Optionally pass --description or --partition command line flags. The server listens on stdio for MCP messages and can be configured in Cursor via a mcp.json file or shell script, or in Claude Desktop via claude_desktop_config.json.

Key features of Ragie Model Context Protocol Server

Single retrieve tool for querying the knowledge base.
Parameters: query (string), topK (optional, default 8), rerank (optional, default true), recencyBias (optional, default false).
Returns an array of content chunks with matching text.
Supports custom tool descriptions via --description flag.
Supports partition-scoped queries via --partition flag.
Compatible with Cursor and Claude Desktop MCP clients.

Use cases of Ragie Model Context Protocol Server

Enable AI assistants to search a company knowledge base for answers.
Provide relevant document snippets to language models during conversations.
Integrate Ragie retrieval into automated workflows that use MCP-compatible tools.
Offer context-aware responses in Cursor or Claude Desktop environments.

FAQ from Ragie Model Context Protocol Server

What is the `retrieve` tool and what parameters does it accept?

The retrieve tool searches the Ragie knowledge base. It accepts query (required), topK (optional, default 8), rerank (optional, default true), and recencyBias (optional, default false). It returns an array of content chunks with matching text.

What are the prerequisites and dependencies?

Node.js >= 18 and a valid Ragie API key. The server uses @modelcontextprotocol/sdk, ragie, and zod.

How do I configure the server with Cursor?

Create a mcp.json file in the project’s .cursor folder or in ~/.cursor/ with the command npx -y @ragieai/mcp-server and required environment variables. Alternatively, use a shell script and add it through Cursor Settings > MCP Servers.

How do I configure the server with Claude Desktop?

Add an entry to claude_desktop_config.json (located at ~/Library/Application Support/Claude/ on macOS or %APPDATA%/Claude/ on Windows) with the same command and environment variables, then restart Claude desktop.

Are there any command line options or customizations?

Yes: --description or -d to override the default tool description, and --partition or -p to specify a Ragie partition ID. Both can be used together.

Comments

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