Build AI Agents on N8n
- No credit card required
- 5-minute setup
- SOC 2 Type II certified
Build AI Agents on top of N8n
Build intelligent AI Agents on top of N8n, with Peliqan’s AI data foundation:
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- N8n MCP Server – let Claude, ChatGPT, or any AI client query and update your N8n data
- N8n in n8n AI Agents – build automated workflows that reason on your data
- N8n in Make – trigger AI-powered actions from your N8n events
- Text-to-SQL on N8n – ask questions in plain English, get SQL-powered answers
- N8n RAG – semantic search with out-of-the-box embeddings (vectors)
- N8n Graph RAG – traverse relationships across your data entities
- Unified 360° data – combine N8n with 250+ other sources in one warehouse
N8n MCP Server
Publish a N8n MCP Server with full read and write capabilities.
Peliqan syncs a read-only copy of your N8n data into its built-in warehouse – your AI agents query the cache, your live N8n is never touched. Connect Claude, ChatGPT, or any MCP client and start querying N8n in plain English.
N8n in n8n
Build AI Chatbots and AI Agents in n8n that query your N8n data using Text-to-SQL and perform RAG on N8n documents and records.
Peliqan acts as the data layer – syncing your N8n data, converting natural language to SQL, and returning results your n8n agent can act on.
Implement a “Text to SQL” chatbot on N8n
Implement an AI Chatbot that answers analytical questions on N8n data using Text-to-SQL.
Ask “what were my top 10 customers last quarter?” or “which deals are stalled?” and get instant, accurate answers.
Peliqan converts your question to SQL, runs it against your N8n warehouse, and returns structured results – no SQL knowledge required.
Implement a chatbot with RAG on N8n
Implement RAG (retrieval-augmented generation) on N8n data with Peliqan’s out-of-the-box vector store.
Peliqan automatically creates embeddings of your N8n records, notes, and documents – so your AI agents can search semantically, not just by keywords.
Combine RAG with Text-to-SQL for AI that can both reason on numbers and understand context.
Combine N8n data with 250+ sources
Combine data from N8n with 250+ other connectors in Peliqan’s built-in warehouse.
Build unified 360° views of customers, deals, products, or employees – pulling from N8n, your CRM, ERP, HR systems, and more.
Feed these unified data models to your AI Agents so they can answer cross-functional questions in a single query.
Prepare your N8n data for AI
Access, combine, and report on data from N8n and all your SaaS apps instantly. Gain valuable insights by bringing all your business data together in one place within minutes.
Unify, Automate & Activate Your Data
Connect all your SaaS apps, databases, and spreadsheets into one workspace. Build automations, analytics pipelines, and data apps — all in one place.
Frequently Asked Questions
Why do I need Peliqan for my AI ?
Most AI tools can’t access your N8n data directly. Peliqan solves this by syncing N8n into a built-in data warehouse and exposing it through MCP, Text-to-SQL, and RAG.
Your AI agents get governed, real-time access to N8n data combined with 250+ other sources – without building custom integrations.
Peliqan is the only platform that lets AI agents combine structured SQL queries with semantic RAG search on N8n data in a single context.
How to build an AI agent for N8n ?
There are different ways to build an AI agent that can query data in N8n and take actions in N8n. For example you can build an AI agent in n8n and use Peliqan as the data foundation. Peliqan will sync your N8n data to its built-in data warehouse and allow the AI Agent to perform “Text to SQL” and RAG to answer questions and to perform reasoning on N8n data, combined with data from 250+ other sources.
How can I use N8n in n8n ?
First sign up for a free trial on Peliqan.io, next connect N8n in Peliqan. Once that is done, create an AI agent in n8n and use the Peliqan n8n node in your worflow. Add Peliqan as a “tool” to your AI Agent node, so that the AI agent can query your N8n data using Text to SQL.
How to use RAG with N8n ?
There are different options to use RAG (retrieval augmented generation) in your AI Agent with N8n data. One option is to create a workflow in n8n that fetches all N8n data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.
How to build an MCP Server for N8n ?
Connect N8n in Peliqan, then create an API handler using the built-in MCP template. Expose the N8n tables and actions your AI needs, set role-based permissions, and run pip install mcp-server-peliqan to connect Claude or ChatGPT. Your AI agents query a cached copy of your data – your live N8n is never touched. The full setup takes under 10 minutes.
How do I build an AI chatbot with “Text to SQL” for N8n ?
n8n is a great tool to build AI chatbots that use Text to SQL, to answer any analytical question on your N8n data. Any question will be converted by the AI agent into an SQL query, which is executed by Peliqan on the N8n data in the data warehouse.
How to create embeddings in a vector store for N8n data ?
In order to prepare your N8n data for RAG, you need to create embeddings and store them in a vector store. This can be done by creating a workflow in n8n that fetches all N8n data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.
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