Build AI Agents on GoCardless
- No credit card required
- 5-minute setup
- SOC 2 Type II certified
Build AI Agents on top of GoCardless
Build intelligent AI Agents on top of GoCardless, with Peliqan’s AI data foundation:
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- GoCardless MCP Server – let Claude, ChatGPT, or any AI client query and update your GoCardless data
- GoCardless in n8n AI Agents – build automated workflows that reason on your data
- GoCardless in Make – trigger AI-powered actions from your GoCardless events
- Text-to-SQL on GoCardless – ask questions in plain English, get SQL-powered answers
- GoCardless RAG – semantic search with out-of-the-box embeddings (vectors)
- GoCardless Graph RAG – traverse relationships across your data entities
- Unified 360° data – combine GoCardless with 250+ other sources in one warehouse
GoCardless MCP Server
Publish a GoCardless MCP Server with full read and write capabilities.
Peliqan syncs a read-only copy of your GoCardless data into its built-in warehouse – your AI agents query the cache, your live GoCardless is never touched. Connect Claude, ChatGPT, or any MCP client and start querying GoCardless in plain English.
GoCardless in n8n
Build AI Chatbots and AI Agents in n8n that query your GoCardless data using Text-to-SQL and perform RAG on GoCardless documents and records.
Peliqan acts as the data layer – syncing your GoCardless data, converting natural language to SQL, and returning results your n8n agent can act on.
Implement a “Text to SQL” chatbot on GoCardless
Implement an AI Chatbot that answers analytical questions on GoCardless 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 GoCardless warehouse, and returns structured results – no SQL knowledge required.
Implement a chatbot with RAG on GoCardless
Implement RAG (retrieval-augmented generation) on GoCardless data with Peliqan’s out-of-the-box vector store.
Peliqan automatically creates embeddings of your GoCardless 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 GoCardless data with 250+ sources
Combine data from GoCardless with 250+ other connectors in Peliqan’s built-in warehouse.
Build unified 360° views of customers, deals, products, or employees – pulling from GoCardless, 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 GoCardless data for AI
Access, combine, and report on data from GoCardless 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 GoCardless data directly. Peliqan solves this by syncing GoCardless 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 GoCardless 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 GoCardless data in a single context.
How to build an AI agent for GoCardless ?
There are different ways to build an AI agent that can query data in GoCardless and take actions in GoCardless. For example you can build an AI agent in n8n and use Peliqan as the data foundation. Peliqan will sync your GoCardless 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 GoCardless data, combined with data from 250+ other sources.
How can I use GoCardless in n8n ?
First sign up for a free trial on Peliqan.io, next connect GoCardless 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 GoCardless data using Text to SQL.
How to use RAG with GoCardless ?
There are different options to use RAG (retrieval augmented generation) in your AI Agent with GoCardless data. One option is to create a workflow in n8n that fetches all GoCardless 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 GoCardless ?
Connect GoCardless in Peliqan, then create an API handler using the built-in MCP template. Expose the GoCardless 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 GoCardless is never touched. The full setup takes under 10 minutes.
How do I build an AI chatbot with “Text to SQL” for GoCardless ?
n8n is a great tool to build AI chatbots that use Text to SQL, to answer any analytical question on your GoCardless data. Any question will be converted by the AI agent into an SQL query, which is executed by Peliqan on the GoCardless data in the data warehouse.
How to create embeddings in a vector store for GoCardless data ?
In order to prepare your GoCardless 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 GoCardless data from Peliqan and stores it in Supabase as a vector store, with embeddings created using e.g. OpenAI.
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