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MCP Server

by ragieai

Retrieves relevant content from a Ragie knowledge base through one MCP search tool over standard input/output.

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Install MCP Server

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "ragieai-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@ragieai/mcp-server"
      ],
      "env": {
        "RAGIE_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Automated check passed— started and listed 1 tools correctly (9d ago).

Overview

The ragieai/mcp-server MCP server exposes Ragie knowledge-base retrieval to MCP-compatible clients through stdio. Its single `retrieve` tool searches for relevant content chunks and supports result limits, reranking, and recency preferences. Use it when an agent needs context from a Ragie knowledge base, including knowledge assembled from sources such as Google Drive, Notion, or JIRA. This repository is deprecated because Ragie now provides MCP natively through a streamable HTTP server.

Use cases

  • Search a Ragie knowledge base from Claude Desktop
  • Retrieve company context inside Cursor
  • Favor recent documents during knowledge-base searches
  • Limit or rerank retrieved content chunks

Key features

  • Ragie knowledge-base retrieval
  • Single `retrieve` MCP tool
  • Configurable result count and reranking
  • Optional recency bias
  • Partition selection
  • stdio transport

Tools1

What MCP Server lets your agent do. Expand a tool for its parameters.

Verified live~440 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

23/24 checks healthy over the last 84d

What it can do

From the 1 tool this server returned when we ran it.

Read-only tools · 1
Network at startup3 connections
Files written at startupNone
Install scriptsprepare
npm provenanceNot published
Package age596 days
Maintainers3

Observed 2026-10-24 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 13d ago via OSV.dev · @ragieai/mcp-server (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars90Stargazers on the source repository.
npm downloads195Package downloads in the last 30 days.
Last commit9mo agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed1Callable tools this server registers over MCP.

How MCP Server works

What ragieai/mcp-server does

The ragieai/mcp-server MCP server gives an MCP client access to retrieval from a Ragie knowledge base. It is intended for applications such as Claude Desktop and Cursor, where an agent can search indexed organizational information during a conversation.

The repository exposes one MCP tool, retrieve. That tool accepts a text query and returns matching content chunks from the knowledge base. The available search controls let the caller set a maximum result count, request reranking, and optionally favor newer information.

The knowledge base may contain information drawn from connected systems such as Google Drive, Notion, and JIRA, but this repository does not provide separate MCP tools for those systems. Retrieval is performed through Ragie.

How it works

The process communicates with an MCP client over standard input/output. When started, it reads MCP protocol messages from stdin and writes responses to stdout. A Ragie API key authorizes requests to the Ragie service.

The retrieve tool requires a query string. topK controls the maximum number of returned results and defaults to 8. rerank defaults to true and controls whether the search attempts to keep the most relevant information. recencyBias defaults to false and controls whether newer material receives preference.

The ragieai/mcp-server MCP server can also receive a partition identifier at startup. This allows queries to target a specified Ragie partition. The tool description can be replaced with custom text using a command-line option.

This repository is no longer required for new Ragie MCP deployments. The README directs users to Ragie’s native streamable HTTP MCP server instead. Existing users evaluating this package should account for that status before adopting it.

Setup and configuration

Node.js 18 or newer and a Ragie API key are required. The only required environment variable is RAGIE_API_KEY. The package can be launched with npx, for example:

bash
RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server

Use --partition or -p to provide a Ragie partition ID. Use --description or -d to replace the default description shown for the tool. Both options can be supplied together.

Cursor can load the server from a project-level or user-level mcp.json file, or through a shell script registered in its MCP settings. Claude Desktop uses claude_desktop_config.json; after changing that file, restart the application so the server becomes available.

Tools and capabilities

The ragieai/mcp-server MCP server provides:

  • retrieve: searches the Ragie knowledge base and returns matching text chunks.
  • query: supplies the search text for retrieve.
  • topK: limits the number of results, with a default of 8.
  • rerank: enables or disables relevance reranking, enabled by default.
  • recencyBias: optionally favors more recent information, disabled by default.
  • Partition targeting through the --partition startup option.

Limitations and notes

Only the retrieve tool is documented. The server does not expose documented tools for adding, editing, or deleting knowledge-base content, and it does not provide separate tools for Google Drive, Notion, or JIRA.

The package uses stdio rather than serving MCP over HTTP. The README marks the project as no longer needed because Ragie now supports MCP natively with a streamable HTTP server. The documented implementation is written in TypeScript and uses the MCP SDK, the Ragie client library, and Zod for runtime validation.

The project is released under the MIT License.

Read the full README View source on GitHub

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Frequently Asked Questions about MCP Server

ragieai/mcp-server is an MCP server that connects MCP-compatible clients to a Ragie knowledge base through stdio. Its main tool, `retrieve`, searches for relevant content chunks and supports result limits, reranking, recency bias, and optional partition targeting. The repository is deprecated because Ragie now offers native streamable HTTP MCP support.

Install it by running `RAGIE_API_KEY=your_api_key npx @ragieai/mcp-server` with Node.js 18 or newer. Set the required `RAGIE_API_KEY` environment variable, then add the command to an MCP client configuration such as Cursor or Claude Desktop.

Yes, ragieai/mcp-server works with Cursor through an MCP configuration file or a registered shell script. Define the `npx` command, pass the optional `--partition` argument if needed, and provide `RAGIE_API_KEY` in the environment configuration.

Yes, ragieai/mcp-server works with Claude Desktop through `claude_desktop_config.json`. Add the server command and API key to the configuration, optionally specify a partition, and restart Claude Desktop.

The `retrieve` tool returns an array of matching content chunks from the Ragie knowledge base. It accepts a query and optional `topK`, `rerank`, and `recencyBias` parameters to control result count, relevance reranking, and preference for recent information.

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