npm package: @s6s/mcp-server
Description: MCP server for S6S.ai — deploy, manage, and monitor workflows from any AI agent
Latest version: 0.1.0

# S6S MCP Server

MCP (Model Context Protocol) server for [S6S.ai](https://s6s.ai) — the workflow engine that AI agents use. Deploy, manage, and monitor persistent multi-step workflows from any MCP-compatible AI agent.

## What it does

S6S turns natural language automation requests into reliable, observable workflows. This MCP server gives your AI agent the ability to:

- **Deploy workflows** — describe what you want automated, the agent builds and deploys it
- **Monitor runs** — check status, view step-by-step results, debug failures
- **Manage workflows** — list, cancel, redeploy with changes

Works with OpenClaw, Claude Desktop, Cursor, and any MCP-compatible client.

## Quick Start

### 1. Get an S6S API key

Sign up at [s6s.ai](https://s6s.ai), go to **API Keys**, and create a key.

### 2. Install

```bash
npm install -g @s6s/mcp-server
```

Or run directly with npx:
```bash
npx @s6s/mcp-server
```

### 3. Configure your AI agent

Set two environment variables:

| Variable | Required | Description |
|---|---|---|
| `S6S_API_KEY` | Yes | Your S6S API key (starts with `s6s_`) |
| `S6S_BASE_URL` | No | API URL (defaults to `https://s6s.ai`) |

## Setup by Platform

### OpenClaw

Add as an MCP plugin in your OpenClaw configuration:

```json
{
  "mcpServers": {
    "s6s": {
      "command": "npx",
      "args": ["@s6s/mcp-server"],
      "env": {
        "S6S_API_KEY": "s6s_your_key_here",
        "S6S_BASE_URL": "https://s6s.ai"
      }
    }
  }
}
```

### Claude Desktop

Add to `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or `%APPDATA%\Claude\claude_desktop_config.json` (Windows):

```json
{
  "mcpServers": {
    "s6s": {
      "command": "npx",
      "args": ["@s6s/mcp-server"],
      "env": {
        "S6S_API_KEY": "s6s_your_key_here",
        "S6S_BASE_URL": "https://s6s.ai"
      }
    }
  }
}
```

### Cursor

Add to `.cursor/mcp.json` in your project:

```json
{
  "mcpServers": {
    "s6s": {
      "command": "npx",
      "args": ["@s6s/mcp-server"],
      "env": {
        "S6S_API_KEY": "s6s_your_key_here",
        "S6S_BASE_URL": "https://s6s.ai"
      }
    }
  }
}
```

## Available Tools

| Tool | Description |
|---|---|
| `s6s_get_catalog` | Discover all node types, triggers, expressions, and flow syntax |
| `s6s_deploy_workflow` | Deploy a workflow from a Recipe JSON — single call, auto-runs |
| `s6s_get_run_status` | Check run progress and step-by-step results |
| `s6s_list_workflows` | List all deployed workflows |
| `s6s_list_runs` | List recent runs with optional status filter |
| `s6s_cancel_run` | Cancel an active run |
| `s6s_list_credentials` | List connected service credentials |

## Example

Tell your AI agent:

> "Create a workflow that fetches the Hacker News front page every hour and posts the top story to Slack"

The agent will:
1. Call `s6s_get_catalog` to learn available node types
2. Build a Recipe with a schedule trigger, HTTP fetch, transform, and Slack post
3. Call `s6s_deploy_workflow` to deploy and start it
4. S6S runs it persistently — survives restarts, retries on failure, fully observable

## Recipe Format (what agents send)

```json
{
  "name": "HN to Slack",
  "trigger": { "type": "schedule", "config": { "cron": "0 * * * *" } },
  "steps": [
    { "ref": "fetch_hn", "action": "http", "config": { "url": "https://hacker-news.firebaseio.com/v0/topstories.json", "method": "GET" } },
    { "ref": "get_top", "action": "http", "config": { "url": "https://hacker-news.firebaseio.com/v0/item/{{fetch_hn.output.body[0]}}.json", "method": "GET" } },
    { "ref": "notify", "action": "slack", "config": { "channel": "#news", "textTemplate": "Top HN: *{{get_top.output.body.title}}*\n{{get_top.output.body.url}}" } }
  ],
  "flow": ["fetch_hn", "get_top", "notify"]
}
```

## Links

- [S6S.ai](https://s6s.ai) — Sign up and manage workflows
- [GitHub](https://github.com/Sawan6/S6S-ai) — Source code