Run a self-hosted multi-channel AI assistant with Claude, Gemini and Gmail

n8nClaw — Self-Hosted AI Assistant

A lightweight, self-hosted AI assistant built entirely in n8n. Multi-channel messaging (Telegram, WhatsApp, Gmail), persistent memory, task management, and autonomous work — all in a single visual workflow.

Inspired by OpenClaw.

What It Does

n8nClaw is a personal AI assistant that lives inside n8n. It connects to your messaging apps, remembers past conversations, manages tasks, and can work autonomously on your behalf.

Core capabilities:

• Multi-channel messaging — talk to your assistant via Telegram, WhatsApp, or Gmail
• Persistent memory — conversations are summarized, embedded, and stored in a Supabase vector database for long-term recall
• Task management — create, track, and complete tasks and subtasks using n8n data tables
• Autonomous heartbeat — an hourly trigger lets the agent check in, process pending tasks, and act on its own
• Media handling — voice messages, images, and documents sent via Telegram are processed by Gemini models
• Sub-agents — delegate work to specialized agents for research, email management, document management, and tiered workers

How It Works

1. Triggers & Input Processing

Four triggers feed into the agent:

• Telegram Trigger — receives text, voice, images, and documents
• WhatsApp Webhook — receives text messages via Evolution API
• Gmail Trigger — polls for new emails every minute
• Hourly Heartbeat — scheduled trigger for autonomous task processing

Each trigger filters messages (e.g., by Telegram chat ID or phone number), fetches the user profile from an Init data table, and normalizes the input into a standard format (user_message, system_prompt, last_channel).

2. Core AI Agent (n8nClaw)

The central agent uses Claude Sonnet 4.5 (via OpenRouter) with a 15-message Postgres chat memory window. It receives the normalized input and decides how to respond — using tools, delegating to sub-agents, or replying directly.

3. Tools

The agent has direct access to:

• Task & Subtask management — CRUD operations on n8n data tables
• User profile updates — persist learned information about the user
• Supabase Vector Store — RAG queries against past conversation summaries

4. Sub-Agents

Specialized agents handle domain-specific work:

Agent	Model	Purpose
Research Agent	Gemini 3 Flash	Web research via Tavily + Wikipedia
Email Manager	Claude Haiku 4.5	Gmail operations (read, reply, send, delete, search)
Document Manager	Claude Haiku 4.5	Google Docs/Drive operations
Worker 1	Claude Haiku 4.5	Simple tasks
Worker 2	Claude Sonnet 4.5	Mid-level work
Worker 3	Claude Opus 4.6	Complex reasoning

5. Output Routing

A Switch node routes the agent's response back to the originating channel (Telegram or WhatsApp).

6. Long-Term Memory Pipeline

A separate scheduled flow runs periodically to:

1. Pull new chat history from Postgres
2. Aggregate and summarize conversations (Haiku 4.5)
3. Generate embeddings (OpenAI)
4. Store in Supabase vector database for future RAG retrieval

Setup Steps

Step 1: Import the Workflow

1. Open n8n
2. Go to Workflows → Import from File
3. Select the n8nClaw.json file

Step 2: Create Data Tables

Create three n8n data tables:

Init Table (user profile):

Column	Type
username	string
soul	string
user	string
heartbeat	string
last_channel	string
last_vector_id	number

Tasks Table:

Column	Type
task_name	string
task_details	string
task_complete	boolean
Is_recurring	boolean

Subtasks Table:

Column	Type
parent_task_id	string
subtask_name	string
subtask_details	string
subtask_complete	boolean

Step 3: Set Up Supabase Vector Store

Create a documents table in Supabase with the pgvector extension enabled. The table should match the schema expected by n8n's Supabase Vector Store node (include a match_documents function).

Step 4: Configure Credentials

Set up the following credentials in n8n (only configure the channels and services you plan to use):

Credential	Required For
Telegram Bot API	Telegram channel
OpenRouter API	All AI models
Postgres	Chat memory
Supabase	Vector store / RAG
OpenAI API	Embeddings
Gmail OAuth2	Email management
Evolution API	WhatsApp
Google AI (Gemini)	Media processing
Google Docs/Drive OAuth2	Document management
Tavily API	Web search (Research Agent)

Step 5: Update Placeholders

Search the workflow for YOUR_ and replace with your actual values:

Placeholder	Replace With
YOUR_USERNAME	Your chosen username
YOUR_TELEGRAM_CHAT_ID	Your Telegram chat ID
YOUR_PHONE	Your phone number (WhatsApp)
YOUR_EVOLUTION_INSTANCE	Your Evolution API instance name
YOUR_*_TABLE_ID	IDs of the data tables from Step 2
YOUR_*_CREDENTIAL_ID	Auto-populated when connecting credentials
YOUR_PROJECT_ID	Your n8n project ID

Step 6: Activate

1. Connect all credentials in the n8n UI
2. Point data table nodes to your tables
3. Update filter nodes with your Telegram chat ID / WhatsApp number
4. Activate the workflow