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Ragie MCP Server

@andyciggy

Basic information

Category

Other

License

MIT license

Transports

stdio

Author

andyciggy

About Ragie MCP Server

No overview available yet

Ragie MCP Server 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"
      }
    }
  }
}

Ragie MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

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.

Frequently asked questions

1

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.

2

What are the prerequisites and dependencies?

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

3

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.

4

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.

5

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.

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