Skip to content
FlowHubFluxonLab
A
AI Automationfree

Access Control for AI Agents (RBAC) using Airtable and Telegram

by Marioadapted from n8n official workflow galleryUpdated Aug 2026
RequiresAAI AgentAirtableAirtableCalculatorCalculatorCall n8n Workflow ToolCall n8n Workflow ToolCode ToolCode ToolHTTP Request ToolHTTP Request ToolLangChain CodeLangChain CodeOpenAI Chat ModelOpenAI Chat ModelSSimple MemoryTelegramTelegramWikipediaWikipedia
Share Post Share
MBSimple MemoryOpenAI Chat ModelOpenAI Chat Mod…CoCheck permissionsCheck permissio…Telegram TriggerSeSet inputGet user permissionsGet user permis…EWWhen Executed by Another WorkflowWhen Executed b…SeSettingsOpenAI Chat Model1OpenAI Chat Mod…MBSimple Memory1CoCheck permissions1Check permissio…TClist_granted_roleslist_granted_ro…TClist_allowed_toolslist_allowed_to…TCcalculatorTWWikipediaTHget_coordinatesTHget_weatherTWweather_agentAgWeather AgentIfUnknown userReply: unknown userReply: unknown …Reply with resultsReply with resu…AgMain Agent1234567891011121314
1/5
FLOWS
STEPS · 14
Starts on a Telegram event

Purpose This workflow allows granular control over the access to tools connected to AI Agents (including Multi-Agent setups) using Role Based Access Control. Demo & Explanation How it works User permissions are managed in Airtable where every restricted AI tool is listed by name and connected via roles to users Requests to the Main Agent can be sent through a Telegram message (can be replaced by Whatsapp, IMAP or similar) On every request the Telegram username is used to query a list of all allowed tools which are linked in Airtable A LangChain Code node is used to compare that list against the connected tools Every tool which is not permitted to be used is being replaced by a tool, which has a status response, telling the Agent to return a message to the user, that he is not authorized to use the tool Otherwise allowed tools are passed through to the Agent, as if they were connected directly to the Agent The parameters can also be passed to a sub-agent called as a sub-workflow where permissions can be checked the same way Every response is sent back to the same Telegram conversation Setup Clone the workflow and select the belonging credentials.

Tags

n8nreference-onlyagentairtablelm-chat-open-aimemory-buffer-windowtelegramtool-calculatortool-codetool-http-requesttool-wikipediatool-workflow
Connects
AAI AgentairtableAirtablecalculatorCalculatorcalln8nworkflowtoolCall n8n Workflow ToolcodetoolCode ToolhttprequesttoolHTTP Request Tool
CategoryAI Automation
Triggermanual
Complexityadvanced
Nodes23
AddedMay 11, 2025

Related workflows

See all AI Automation
AopenaichatmodelserpapigooglesearchS
free

AI chatbot that can search the web

This workflow is designed for dynamic and intelligent conversational capabilities. It incorporates OpenAI's GPT-4o model for natural language understanding and generation. Additional tools include SerpAPI and Wikipedia for enriched, data-driven responses. The workflow is triggered manually, and utilizes a 'Window Buffer Memory' to maintain the context of the last 20 interactions for better conversational continuity. All these components are orchestrated through n8n nodes, ensuring seamless interconnectivity. To use this template, you need to be on n8n version 1.50.0 or later.

by n8n Team
AopenaichatmodelserpapigooglesearchS
free

Slack chatbot powered by AI

This workflow offers an effective way to handle a chatbot's functionality, making use of multiple tools for information retrieval, conversation context storage, and message sending. It's a setup tailored for a Slack environment, aiming to offer an interactive, AI-driven chatbot experience. Note that to use this template, you need to be on n8n version 1.19.4 or later.

by n8n Team
Acodetoollangchaincodeopenaichatmodel
free

Custom LangChain agent written in JavaScript

This workflow has multiple functionalities. It starts with a manual trigger, "When clicking 'Execute Workflow'", that activates two separate paths. The first path takes a preset string "Tell me a joke" and processes it through a custom Language Learning Model (LLM) chain node. This node interacts with an OpenAI node for query processing. The second path takes another preset string "What year was Einstein born?" and passes it to an "Agent" node. This agent further interacts with a Chat OpenAI node and a custom Wikipedia node to produce the required information. The workflow uses both built-in and custom nodes, and integrates with OpenAI for both paths. It's built for experimenting with language models, specifically in the context of conversational agents and information retrieval. Note that to use this template, you need to be on n8n version 1.19.4 or later.

by n8n Team