Blinkbox MCP Server

BlinkBox

Open-source automation platform (Zapier / Make / n8n alternative) with a native MCP server — connect Claude Code, Cursor or ChatGPT and let the agent build, run and debug your workflows.

Free hosted tier at blinkbox.net (no card) · self-host with Node 22 + MongoDB + Redis · MIT.

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What it does

• MCP server — the whole platform is exposed over the Model Context Protocol (Streamable HTTP). Your coding agent lists, creates, runs, activates and debugs workflows with tool calls — see Use it from Claude Code
• Agent skill — a SKILL.md that teaches the agent node fields, expression syntax and execution rules, so a working flow takes ~4 tool calls instead of ~12 of guessing
• Drag-and-drop canvas — everything the agent builds is a normal workflow you can open and edit visually
• AI Agents — LLM nodes that reason over data and output structured results
• Headless scraping — full Chromium pool, defeats anti-bot, renders JavaScript
• Code sandbox — write JavaScript in an isolated V8 sandbox with memory limits
• 250+ integrations — Gmail, Slack, Stripe, GitHub, Notion, Airtable, Shopify, and more
• Encrypted credential vault — AES-256-GCM; secrets never leave the server decrypted

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Use it from Claude Code, Cursor or ChatGPT (60 seconds)

1. Sign up at blinkbox.net → Dashboard → MCP → create an API key.

2. Add the server to your client:

   # Claude Code
   claude mcp add --transport http blinkbox https://mcp.blinkbox.net/mcp \
     --header "Authorization: Bearer <your key>"
   

   // Cursor / Claude Desktop / any client that takes a JSON config
   {
     "mcpServers": {
       "blinkbox": {
         "url": "https://mcp.blinkbox.net/mcp",
         "headers": { "Authorization": "Bearer <your key>" }
       }
     }
   }
   

   Clients that can't send headers can pass the key in the URL instead: https://mcp.blinkbox.net/mcp?key=<your key>.

3. (Recommended) install the skill so the agent knows the node catalog and expression syntax:

   mkdir -p ~/.claude/skills/blinkbox && curl -fsSL \
     https://raw.githubusercontent.com/blinkboxhq/Blinkbox/main/.claude/skills/blinkbox/SKILL.md \
     -o ~/.claude/skills/blinkbox/SKILL.md
   

4. Ask for what you want:

   "Every morning at 8, find dentists in Berlin on OpenStreetMap that list a website, email and phone, dedupe against my Google Sheet and append the new ones."

   The agent calls create_automation, runs it with run_automation, reads get_execution_logs when something fails, and activate_automation when it's green. OAuth apps (Google, Slack, Notion…) are connected once by you in the dashboard — the agent never sees your tokens.

Tools: list_automations · get_automation · create_automation · run_automation · activate_automation · deactivate_automation · rename_automation · delete_automation · list_executions · get_execution · get_execution_logs · list_nodes · get_node · list_node_actions · list_credentials · create_credential · blinkbox_api_get · blinkbox_api

Self-hosting? The same server is at <your backend>/api/mcp — create keys in your own dashboard.

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Stack

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Local setup

Prerequisites

• Node.js ≥ 22
• MongoDB Atlas cluster (or local MongoDB)
• Redis (local or Upstash)

1. Clone

git clone https://github.com/blinkboxhq/Blinkbox.git
cd Blinkbox
npm install

2. Configure environment

cp apps/backend/.env.example apps/backend/.env

Edit apps/backend/.env — at minimum you need:

MONGODB_URI=mongodb+srv://...
REDIS_URL=redis://localhost:6379
JWT_SECRET=your-32-char-secret
ENCRYPTION_KEY=your-exactly-32-char-key
ANTHROPIC_API_KEY=sk-ant-...          # enables the AI workflow builder behind create_automation

3. Run

# Terminal 1 — backend (port 3000)
cd apps/backend && npm run dev

# Terminal 2 — frontend (port 5174)
cd apps/frontend && npm run dev

Open http://localhost:5174.

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Environment variables

Required

AI (at least one recommended)

OAuth integrations (optional)

Deployment

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Architecture

┌─────────────────────────────────────────────────────┐
│                    Frontend (Vite)                  │
│  Dashboard · Workspace Canvas · MCP keys            │
└───────────────────────┬─────────────────────────────┘
                        │ REST API
┌───────────────────────▼─────────────────────────────┐
│                Backend (Express)                    │
│  Auth · Automations · Executions · Credentials      │
│  MCP server · AI builder · OAuth · Webhooks         │
└──────────┬──────────────────┬───────────────────────┘
           │                  │
    ┌──────▼──────┐    ┌──────▼──────┐
    │  MongoDB    │    │    Redis    │
    │  Atlas      │    │   Queues   │
    └─────────────┘    └──────┬──────┘
                              │
                    ┌─────────▼───────────┐
                    │  Execution Workers  │
                    │  (4 cursor cells)   │
                    │  Chromium pool      │
                    └─────────────────────┘

Execution engine

Workflows run as cursor-based state machines. Each execution is a MongoDB document with a cursor array. Workers claim cursors atomically via arrayFilters, run the node handler, advance the cursor, and release. Redis queues decouple trigger fan-out from execution. A resumer process recovers crashed executions every 5 seconds.

Node system

Every integration is a node with two halves:

• Frontend (nodeRegistry.js) — config panel, icon, label, category
• Backend (nodes/) — stateless handler async (config, context) => result

The same backendType key connects both sides. 250+ nodes are registered.

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AI workflow builder

create_automation (the MCP tool) hands your description to a server-side builder:

"When a new Stripe payment comes in, look up the customer in HubSpot, and send a Slack alert to #revenue"

The builder calls Claude with the node knowledge base and forced tool use, and returns a fully configured, canvas-correct workflow — real field values, variable chaining ({{trigger.data.from}}), node positions — as a draft you can run, inspect and activate from the agent or the UI.

Provider fallback chain: Anthropic → Groq → Gemini

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Security

• JWT auth on all API routes, workspace-scoped queries
• AES-256-GCM credential encryption (key never stored in DB)
• SSRF guard on all outbound HTTP requests
• Code sandbox: isolated V8 with memory/time limits (isolated-vm)
• Shell tool nodes gated behind ENABLE_SHELL_TOOLS=true (off by default)
• OAuth state tokens (CSRF protection), postMessage to explicit origins only
• Rate limiting on webhook triggers (Redis-backed, survives restarts)

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Deployment on Railway

1. Create a Railway project, add the repo
2. Set all required env vars in Railway dashboard
3. Set BACKEND_PUBLIC_URL to your Railway backend URL
4. Register that URL as an OAuth redirect URI in Google Cloud Console (if using Gmail)

The nixpacks.toml in apps/backend/ installs Chromium and all native deps automatically.

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License

MIT