GitHub - jolks/goto-assistant: Personal AI assistant that remembers, runs scheduled tasks, and works on WhatsApp

Personal AI assistant that remembers past conversations, runs scheduled tasks, and works on both web and WhatsApp. Supports Claude, OpenAI, and OpenAI-compatible providers (Gemini, Groq, Ollama, etc.).

Quick Start

Open http://localhost:3000 — first run redirects to setup page for API key config.

Requirements

• Node.js 20.11 or later — npx runs the app and most MCP servers
• uv — uvx runs the time MCP server (Python-based)
• Anthropic, OpenAI, or OpenAI-compatible API key (Gemini, Groq, Ollama, etc.)

Data Storage

All data (config, conversations, uploads) stored in ~/.goto-assistant/. Custom location: GOTO_DATA_DIR=/path/to/data npx goto-assistant

Custom Port

PORT=3001 npx goto-assistant

Why goto-assistant?

One command, no Docker, no framework — just MCP. Chat from the web or WhatsApp.

        You
         │
    chat / ask
         │
         ▼
   ┌──────────────────┐
   │    AI Assistant  │
   └──┬──┬──┬──┬──┬──┘
      │  │  │  │  │
      │  │  │  │  └── create / update / run /  ──▶ ┌──────────────┐
      │  │  │  │      schedule / get results       │     Cron     │──── ┐
      │  │  │  └───── read / write ────────────▶   ├──────────────┤     │
      │  │  │                                      │    Files     │   AI tasks
      │  │  └──────── remember / recall ───────▶   ├──────────────┤   w/ MCP
      │  │                                         │    Memory    │◀── access
      │  └── recall conversations & task runs ──▶  ├──────────────┤
      │                                            │   Episodic   │
      │                                            ├──────────────┤
      └────────── do anything ─────────────────▶   │  + your MCP  │
                                                   │   servers    │
                                                   └──────────────┘

That one npx command gives you an AI assistant that can remember across conversations, search past interactions, manage your files, and run tasks on a schedule or on-demand — all through the standard MCP protocol. Add any MCP server to extend it further.

See it in action

Setup

Tasks

Data Privacy

goto-assistant connects directly to AI providers using your own API keys. Both Anthropic and OpenAI have clear policies that API data is not used for model training by default:

Anthropic (Commercial Terms; Privacy Center):

"Anthropic may not train models on Customer Content from Services."

"By default, we will not use your inputs or outputs from our commercial products to train our models."

OpenAI (Platform Data Controls; Enterprise Privacy):

"Data sent to the OpenAI API is not used to train or improve OpenAI models (unless you explicitly opt in to share data with us)."

"We do not train our models on your data by default."

Your conversations and data stay between you and the provider's API. All local data is stored on your machine:

• goto-assistant: conversations, config, uploads, and WhatsApp auth in ~/.goto-assistant/
• mcp-cron: tasks and results in ~/.mcp-cron/

WhatsApp Integration

Chat with the assistant directly from WhatsApp — no extra apps, no Docker, no webhooks needed.

Uses Baileys (WhatsApp Web multi-device protocol) running in-process. Enable it in the setup wizard or toggle it on the setup page, scan the QR code once, and you're connected. Auth persists across restarts.

Messages go through the same AI pipeline as the web chat. The agent only responds in your self-chat ("Message yourself") — it never replies to other people messaging your number.

Architecture

Browser and WhatsApp clients connect to server.ts (WebSocket + REST), which routes messages through router.ts to the Claude or OpenAI agent SDK. Agents access MCP servers (memory, filesystem, cron, messaging, etc.) for extended capabilities. Messaging flows through a channel registry — the mcp-messaging MCP server proxies tool calls to POST /api/messaging/send, which routes to the appropriate channel (WhatsApp, etc.). The episodic-memory MCP server provides full-text search over past conversations and task results using SQLite FTS5, enabling the agent to recall prior interactions.

See docs/architecture.md for the full architecture diagram.

Development Setup

1. Install dependencies:

2. Start the development server:

3. Open http://localhost:3000 — you'll be redirected to the setup page on first run to configure your AI provider and API key.

4. Lint and test:

Configuration

App configuration is stored in data/config.json (created on first setup). MCP server configuration is stored separately in data/mcp.json. Environment variables override file config:

• ANTHROPIC_API_KEY — API key for Claude
• OPENAI_API_KEY — API key for OpenAI (also used for OpenAI-compatible providers)

For OpenAI-compatible providers, set the base URL in the setup page (e.g. https://generativelanguage.googleapis.com/v1beta/openai for Gemini). The app auto-detects known gateways and switches to the Chat Completions API when needed.

MCP Servers

The assistant comes pre-configured with these MCP servers:

Add your own through the setup page — either via the form or by asking the setup wizard AI chat — or by editing data/mcp.json directly. Any MCP server that supports stdio transport will work — browse the MCP server directory for more.