MCP Setup - Rayify

The Rayify MCP server (@rayify-ai/mcp) is the slim-8 integration surface designed for LLM-driven workflows. It exposes 4 pull tools + 4 push tools + 3 guided prompts.

Install

The MCP server runs via npx - no install step required:

npx -y @rayify-ai/mcp

Configure your AI client

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "rayify": {
      "command": "npx",
      "args": ["-y", "@rayify-ai/mcp"],
      "env": {
        "RAYIFY_API_KEY": "sk_your_key"
      }
    }
  }
}

Restart Claude Desktop. The Rayify tools appear in the tool list with a hammer icon.

Cursor

Open Cursor Settings → Features → Model Context Protocol → Add MCP Server. Configure:

Name: rayify
Command: npx
Args: -y @rayify-ai/mcp
Env: RAYIFY_API_KEY=sk_your_key

ChatGPT (via custom GPT)

ChatGPT does not yet have native MCP support. Use the TypeScript SDK instead, exposed as a Custom Action.

Generic MCP client

Any client that speaks MCP can connect:

RAYIFY_API_KEY=sk_your_key npx -y @rayify-ai/mcp

The server speaks MCP over stdio.

The 8 tools

Pull (4)

Tool	Purpose
`list_my_projects`	List the workspace’s projects, optionally filtered by status / kind
`get_project`	Pull a project’s full state (questions, reasonings, DecisionPacket) into your context
`get_project_status`	Light status check - pings the project without dragging full state
`search_findings`	Semantic search across the workspace’s project corpus

Push (4)

Tool	Purpose
`create_question`	Add a question to an in-flight project
`create_research_project`	Start a research project from a one-shot brief
`attach_source`	Attach a URL or document to a project’s evidence pack
`create_survey`	Run a list of questions as a multi-agent survey

The 3 guided prompts

Slash-prompts that an MCP client can surface:

Prompt	What it does
`/pull-recent`	Lists the workspace’s 10 most recent projects with their status
`/cite-rayify`	Wraps your current response with a Rayify citation block (links + DecisionPacket excerpt)
`/quick-ask`	Starts a one-shot research project from your current chat context

What’s not in the MCP surface

The MCP server is intentionally slim - heavy authoring lives on the web app (rayify.ai):

Matrix / likert / star_rating question authoring (create_survey accepts string arrays only)
Project editing, deleting, sharing
Agent template editing
Org / billing / settings

If you need any of these, use the SDK or the web app.

Authentication

The MCP server reads RAYIFY_API_KEY from the environment. Pass it via the env block of your MCP client config, never hardcoded. For workspaces with multiple users, provision a per-user API key - the MCP server’s actions are recorded under the key’s owner in the audit log.

What’s next

SDK Setup - for non-AI workflows
API Reference - the underlying REST API

​Install

​Configure your AI client

​Claude Desktop

​Cursor

​ChatGPT (via custom GPT)

​Generic MCP client

​The 8 tools

​Pull (4)

​Push (4)

​The 3 guided prompts

​What’s not in the MCP surface

​Authentication

​What’s next